Deep Learning for Geometry Problem Solving (DL4GPS)

September 14, 2025 · View on GitHub

Awesome License: MIT Survey

This repository is the reading list on A Survey of Deep Learning for Geometry Problem Solving (DL4GPS). We will update the papers after a certain period of time. The current deadline for included papers is April 2025.

  • :large_blue_circle: indicates that the work is not specifically designed for geometry problems.

  • :small_red_triangle: represents geometry tasks other than geometry problem solving.

  • :x: indicates no deep learning method is used.

For more details, please refer to the paper: A Survey of Deep Learning for Geometry Problem Solving.

:bell: If you have any suggestions or notice something we missed, please don't hesitate to let us know. You can directly email Jianzhe Ma (majianzhe@ruc.edu.cn), or post an issue on this repo.

Table of Contents

Surveys

  • Plane Geometry Problem Solving with Multi-modal Reasoning: A Survey, arXiv:2505.14340 [paper]
  • Towards Geometry Problem Solving in the Large Model Era: A Survey, arXiv:2506.02690 [paper]

Tasks and Datasets - Fundamental Tasks

Geometry Diagram Understanding

  • 2D Geometric Shapes Dataset – For Machine Learning and Pattern Recognition, Data in Brief 2020 [paper] [2Dgeometricshapes data]
  • Geoclidean: Few-Shot Generalization in Euclidean Geometry, NeurIPS 2022 [paper] [Geoclidean data]
  • Euclid: Supercharging Multimodal LLMs With Synthetic High-Fidelity Visual Descriptions, arXiv:2412.08737 [paper] [Geoperception data]
  • GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models, arXiv:2412.21036 [paper] [GePBench data]
  • Do Large Language Models Truly Understand Geometric Structures?, ICLR 2025 [paper] [GeomRel data]
  • Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring, arXiv:2412.00846 [paper]
  • Advancing Multimodal LLMs: A Focus on Geometry Problem Solving Reasoning and Sequential Scoring, MMASIA 2024 [paper]
  • G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model, ICLR 2025 [paper] [Geo170K-alignment data]
  • GOLD: Geometry Problem Solver With Natural Language Description, Findings of NAACL 2024 [paper]
  • AutoGeo: Automating Geometric Image Dataset Creation for Enhanced Geometry Understanding, IEEE Trans. Multimedia 2025 [paper] [AutoGeo-100k data]
  • GeoDANO: Geometric VLM with Domain Agnostic Vision Encoder, arXiv:2502.11360 [paper] [VGPR data]
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper] [SynthGeo228K/formalgeo-structure774k data]
  • GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper] [GeoX-alignment data]
  • Decomposing Complex Visual Comprehension Into Atomic Visual Skills for Vision Language Models, NeurIPS 2024 MATH-AI Workshop [paper] [AVSBench data] :large_blue_circle:
  • VisOnlyQA: Large Vision Language Models Still Struggle With Visual Perception of Geometric Information, arXiv:2412.00947 [paper] [VisOnlyQA data] :large_blue_circle:
  • VisNumBench: Evaluating Number Sense of Multimodal Large Language Models, arXiv:2503.14939 [paper] [VisNumBench data] :large_blue_circle:
  • MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams, arXiv:2503.20745 [paper] [MATHGLANCE/GeoPeP data]
  • Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding, Findings of ACL 2025 [paper] [CogAlign-Probing/CogAlign-train data]
  • Retrieving Geometric Information from Images: The Case of Hand-Drawn Diagrams, KDD 2017 [paper] :x:
  • A Novel Geometric Information Retrieval Tool for Images of Geometric Diagrams, ICISE-IE 2020 [paper]
  • A Paradigm of Diagram Understanding in Problem Solving, TALE 2021 [paper] :x:
  • Plane Geometry Diagram Parsing, IJCAI 2022 [paper] [PGDP5K data]
  • Learning to Understand Plane Geometry Diagram, NeurIPS 2022 MATH-AI Workshop [paper] [PGDP5K data]
  • PGDP5K: A Diagram Parsing Dataset for Plane Geometry Problems, ICPR 2022 [paper] [PGDP5K data]
  • Usage of Stacked Long Short-Term Memory for Recognition of 3D Analytic Geometry Elements, ICAART 2022 [paper]
  • Solving Algebraic Problems with Geometry Diagrams Using Syntax-Semantics Diagram Understanding, Computers, Materials & Continua 2023 [paper] :x:
  • Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them, Findings of ACL 2023 [paper] [BBH-geometricshapes data]
  • 2D Shape Detection for Solving Geometry Word Problems, IETE J. Res. 2024 [paper] :x:
  • Slow Perception: Let's Perceive Geometric Figures Step-by-Step, arXiv:2412.20631 [paper] [SP-1 data]
  • Leveraging Two-Level Deep Learning Classifers for 2D Shape Recognition to Automatically Solve Geometry Math Word Problems, PAA 2024 [paper] [GeoCQT data]
  • Tangram: A Challenging Benchmark for Geometric Element Recognizing, arXiv:2408.13854 [paper] [Tangram data]
  • CurveML: A Benchmark for Evaluating and Training Learning-Based Methods of Classification, Recognition, and Fitting of Plane Curves, Visual Comput 2024 [paper] [CurveML data]
  • ElementaryCQT: A New Dataset and Its Deep Learning Analysis for 2D Geometric Shape Recognition, SN Comput. Sci. 2025 [paper] [ElementaryCQT data]
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper] [SynthGeo228K/formalgeo-structure774k data]

Semantic Parsing for Geometry Problem

  • Semantic Parsing of Pre-University Math Problems, ACL 2017 [paper] :x:
  • Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers, EMNLP 2017 [paper] :large_blue_circle: :x:
  • From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems, EMNLP 2017 [paper] :x:
  • Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks, CL 2019 [paper] :x:
  • Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples, ACL 2018 [paper]
  • A Neural Semantic Parser for Math Problems Incorporating Multi-Sentence Information, TALLIP 2019 [paper] :large_blue_circle:
  • Two-step memory networks for deep semantic parsing of geometry word problems, SOFSEM 2020 [paper]
  • Semantic parsing of geometry statements using supervised machine learning on Synthetic Data, NatFoM 2021 CICM Workshop [paper]
  • Cognitive Patterns for Semantic Presentation of Natural-Language Descriptions of Well-Formalizable Problems, RCAI 2021 [paper] :x:
  • Exploration of Formalization Techniques for Geometric Entities in Planar Geometry Proposition Texts, JAIP 2025 [paper]
  • Extracting structured information from the textual description of geometry word problems, NLPIR 2023 [paper] :x:
  • Automatic Extraction of Structured Information from Elementary Level Geometry Questions into Logic Forms, Multimed Tools Appl 2024 [paper] [ElementaryGeometryQA data]
  • Evaluating Automated Geometric Problem Solving With Formal Language Generation on Large Multimodal Models, IEIR 2024 [paper]
  • FGeo-Parser: Autoformalization and Solution of Plane Geometric Problems, Symmetry 2025 [paper]

Geometric Relation Extraction

  • Diagram Understanding in Geometry Questions, AAAI 2014 [paper] :x:
  • Understanding Plane Geometry Problems by Integrating Relations Extracted from Text and Diagram, PSIVT 2017 [paper] [GeoC50 data] :x:
  • Understanding Explicit Arithmetic Word Problems and Explicit Plane Geometry Problems Using Syntax-Semantics Models, IALP 2017 [paper] :x:
  • Automatic Understanding and Formalization of Natural Language Geometry Problems Using Syntax-Semantics Models, IJICIC 2018 [paper] :x:
  • Automatic Understanding and Formalization of Plane Geometry Proving Problems in Natural Language: A Supervised Approach, IJAIT 2019 [paper] :x:
  • GeoRE: A relation extraction dataset for chinese geometry problems, NeurIPS 2021 MATHAI4ED Workshop [paper] [GeoRE data]
  • A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model, IEIR 2022 [paper]
  • Research on Geometry Problem Text Understanding Based on Bidirectional LSTM-CRF, ICDH 2022 [paper]
  • A Knowledge and Semantic Fusion Method for Automatic Geometry Problem Understanding, Appl. Sci. 2025 [paper]

Geometric Knowledge Prediction

  • Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning, ACL 2021 [paper]
  • E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator, CVPR 2024 [paper]
  • GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs, AAAI 2025 [paper] [GNS-260K data]
  • GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning, arXiv:2504.12597 [paper] [GeoSense data]

Tasks and Datasets - Core Tasks

  • UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression, EMNLP 2022 [paper] [UniGeo data]
  • FormalGeo: An Extensible Formalized Framework for Olympiad Geometric Problem Solving, arXiv:2310.18021 [paper] [formalgeo7k/formalgeo-imo data] :x:
  • GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation, EMNLP 2024 [paper] [GeoGPT4V-GPS data]
  • GeoVQA: A Comprehensive Multimodal Geometry Dataset for Secondary Education, MIPR 2024 [paper] [GeoVQA data]
  • Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems With Meta In-Context Learning, LGM3A 2024 [paper] [GeoMath data]
  • Advancing Multimodal LLMs: A Focus on Geometry Problem Solving Reasoning and Sequential Scoring, MMASIA 2024 [paper] [GPSM4K data]
  • Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring, arXiv:2412.00846 [paper] [GPSM4K data]
  • Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning, LGM3A 2024 [paper] [GeoMath data]
  • Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration, arXiv:2504.12773 [paper] [GeoExpand/GeoSynth data]

Geometry Theorem Proving

  • A Paradigm of Diagram Understanding in Problem Solving, TALE 2021 [paper] [Proving2H data] :x:
  • Solving Olympiad Geometry Without Human Demonstrations, Nature 2024 [paper] [IMO-AG-30 data]
  • Wu’s Method Boosts Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry, NeurIPS 2024 MATH-AI Workshop [paper]
  • Proposing and Solving Olympiad Geometry with Guided Tree Search, arXiv:2412.10673 [paper] [MO-TG-225 data]
  • Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2, arXiv:2502.03544 [paper] [IMO-AG-50 data]

Geometric Numerical Calculation

  • Solving Geometry Problems: Combining Text and Diagram Interpretation, EMNLP 2015 [paper] GEOS data] :x:
  • From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems, EMNLP 2017 [paper] [GEOS++ data] :x:
  • Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks, CL 2019 [paper] [GEOS++ data] :x:
  • Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks, *SEM 2017 [paper] [GEOS-OS] :x:
  • Synthesis of Solutions for Shaded Area Geometry Problems, FLAIRS 2017 [paper] [GeoShader data] :x:
  • Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning, ACL 2021 [paper] [Geometry3K data]
  • GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning, Findings of ACL 2021 [paper] [GeoQA data]
  • Solving Solid Geometric Calculation Problems in Text, TALE 2021 [paper] [Geometry3Dcalculation data] :x:
  • Solving Shaded Area Problems by Constructing Equations, AIET 2021 [paper] :x:
  • Sequence to General Tree Knowledge-Guided Geometry Word Problem Solving, ACL-IJCNLP 2021 [paper] [GeometryQA data]
  • An Augmented Benchmark Dataset for Geometric Question Answering through Dual Parallel Text Encoding, COLING 2022 [paper] [GeoQA+ data]
  • Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models, TMLR 2022 [paper] [BIG-bench-IG data] :large_blue_circle:
  • A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram, IJCAI 2023 [paper] [PGPS9K data]
  • Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset, Findings of EMNLP 2023 [paper] [Conic10K data]
  • GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning, ICML 2024 AI4MATH Workshop [paper] [GeomVerse data]
  • E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator, CVPR 2024 [paper] [aug-Geo3K data]
  • GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving, Findings of ACL 2024 [paper] [GeoEval data]
  • R-CoT: Reverse Chain-of-Thought Problem Generation for Geometric Reasoning in Large Multimodal Models, arXiv:2410.17885 [paper] [GeoMM data]
  • An Enhanced Relation-Flow Algorithm for Solving Number Line Problems, IEIR 2024 [paper] [NBLP data] :x:
  • BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models, Findings of ACL 2024 [paper] [G-MATH data]
  • Is Your Model Really a Good Math Reasoner? Evaluating Mathematical Reasoning With Checklist, arXiv:2407.08733 [paper] [MATHCHECK-GEO data]
  • G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model, ICLR 2025 [paper] [ Geo170K-qadata]
  • TrustGeoGen: Scalable and Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving, arXiv:2504.15780 [paper] [GeoTrust data]
  • FGeo-Parser: Autoformalization and Solution of Plane Geometric Problems, Symmetry 2025 [paper] [FormalGeo7K-v2 data]
  • LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL, arXiv:2503.07536 [paper] [VerMulti-Geo data]
  • Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning, arXiv:2503.20752 [paper] [GeoMath-8K data] :large_blue_circle:
  • GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs, AAAI 2025 [paper] [GNS-260K data]
  • GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning, arXiv:2504.12597 [paper] [GeoSense data]
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper] [formalgeo-reasoning238k data]

Tasks and Datasets - Composite Tasks

Mathematical Reasoning

  • Measuring Mathematical Problem Solving With the MATH Dataset, NeurIPS 2021 [paper] [MATH/AMPS data] :large_blue_circle:
  • NUMGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks, ACL 2022 [paper] [NUMGLUE data] :large_blue_circle:
  • Lila: A Unified Benchmark for Mathematical Reasoning, EMNLP 2022 [paper] [Lila data] :large_blue_circle:
  • It Ain’t Over: A Multi-Aspect Diverse Math Word Problem Dataset, EMNLP 2023 [paper] [DMath data] :large_blue_circle:
  • TheoremQA: A Theorem-driven Question Answering Dataset, EMNLP 2023 [paper] [TheoremQA data] :large_blue_circle:
  • M3exam: A multilingual, multimodal, multilevel benchmark for examining large language models, NeurIPS 2023 [paper] [M3Exam data] :large_blue_circle:
  • OlympiadBench: A Challenging Benchmark for Promoting AGI With Olympiad-Level Bilingual Multimodal Scientific Problems, ACL 2024 [paper] [OlympiadBench data] :large_blue_circle:
  • MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts, ICLR 2024 [paper] [MathVista data] :large_blue_circle:
  • MathVerse: Does Your Multi-Modal LLM Truly See the Diagrams in Visual Math Problems?, ECCV 2024 [paper] [MathVerse data] :large_blue_circle:
  • Measuring Multimodal Mathematical Reasoning With MATH-Vision Dataset, NeurIPS 2024 [paper] [MATH-Vision data] :large_blue_circle:
  • MM-MATH: Advancing Multimodal Math Evaluation With Process Evaluation and Fine-Grained Classification, Findings of EMNLP 2024 [paper] [MM-MATH data] :large_blue_circle:
  • We-Math: Does Your Large Multimodal Model Achieve Human-Like Mathematical Reasoning?, arXiv:2407.01284 [paper] [We-Math data] :large_blue_circle:
  • VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning, arXiv:2410.22995 [paper] [VisAidMath data] :large_blue_circle:
  • CMM-Math: A Chinese Multimodal Math Dataset to Evaluate and Enhance the Mathematics Reasoning of Large Multimodal Models, arXiv:2409.02834 [paper] [CMM-Math data] :large_blue_circle:
  • MathScape: Evaluating MLLMs in Multimodal Math Scenarios Through a Hierarchical Benchmark, arXiv:2408.07543 [paper] [MathScape data] :large_blue_circle:
  • VisScience: An Extensive Benchmark for Evaluating K12 Educational Multi-Modal Scientific Reasoning, arXiv:2409.13730 [paper] [VisScience data] :large_blue_circle:
  • Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models, ACL 2024 [paper] [ArXivQA data] :large_blue_circle:
  • ReMI: A Dataset for Reasoning With Multiple Images, NeurIPS 2024 [paper] [ReMI data] :large_blue_circle:
  • Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models, EMNLP Findings 2024 [paper] [MathV360K data] :large_blue_circle:
  • MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models, arXiv:2409.00147 [paper] [MultiMath-300K data] :large_blue_circle:
  • InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning, NeurIPS 2024 MATH-AI Workshop [paper] [InfiMM-WebMath-40B data] :large_blue_circle:
  • MathGLM-Vision: Solving Mathematical Problems With Multi-Modal Large Language Model, arXiv:2409.13729 [paper] [MathVL data] :large_blue_circle:
  • Mathematical Problem Solving in Arabic: Assessing Large Language Models, Procedia Comput. Sci. 2024 [paper] [ArMATH data] :large_blue_circle:
  • M3CoT: A Novel Benchmark for Multi-Domain Multi-Step Multi-Modal Chain-of-Thought, ACL 2024 [paper] [M3CoT data] :large_blue_circle:
  • MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data, arXiv:2406.18321 [paper] [MathOdyssey data] :large_blue_circle:
  • PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition, NeurIPS 2024 [paper] [PutnamBench data] :large_blue_circle:
  • ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models, Findings of ACL 2024 [paper] [ConceptMath data] :large_blue_circle:
  • Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap, arXiv:2402.19450 [paper] [MATH() data] :large_blue_circle:
  • MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark, Findings of ACL 2024 [paper] [MathBench data] :large_blue_circle:
  • HARP: A Challenging Human-Annotated Math Reasoning Benchmark, arXiv:2412.08819 [paper] [HARP data] :large_blue_circle:
  • M3GIA: A Cognition-Inspired Multilingual and Multimodal General Intelligence Ability Benchmark, arXiv:2406.05343 [paper] [M3GIA data] :large_blue_circle:
  • DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving, NeurIPS 2024 [paper] [DART-Math data] :large_blue_circle:
  • MathScale: Scaling Instruction Tuning for Mathematical Reasoning, ICML 2024 [paper] [MathScaleQA data] :large_blue_circle:
  • UTMath: Math Evaluation with Unit Test via Reasoning-to-Coding Thoughts, arXiv:2411.07240 [paper] [UTMath data] :large_blue_circle:
  • MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning, arXiv:2412.12609 [paper] [MultiLingPoT data] :large_blue_circle:
  • System-2 Mathematical Reasoning via Enriched Instruction Tuning, arXiv:2412.16964 [paper] [EITMath data] :large_blue_circle:
  • AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning, arXiv:2411.11930 [paper] [AMATH-SFT data] :large_blue_circle:
  • Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?, arXiv:2503.06252 [paper] [AMATH-SFT data] :large_blue_circle:
  • URSA: Understanding and Verifying Chain-of-Thought Reasoning in Multimodal Mathematics, arXiv:2501.04686 [paper] [MMathCoT-1M data] :large_blue_circle:
  • DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models, ICLR 2025 [paper] [DynaMath data] :large_blue_circle:
  • CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models, AAAI 2025 [paper] [CoMT data] :large_blue_circle:
  • Feynman: Knowledge-Infused Diagramming Agent for Scaling Visual Reasoning Data, openreview 2025 [paper] [Diagramma data] :large_blue_circle:
  • MV-MATH: Evaluating Multimodal Math Reasoning in Multi-Visual Contexts, arXiv:2502.20808 [paper] [MV-MATH data] :large_blue_circle:
  • CMMaTH: A Chinese Multi-modal Math Skill Evaluation Benchmark for Foundation Models, COLING 2025 [paper] [CMMaTH data] :large_blue_circle:
  • Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning, AAAI 2025 [paper] [Math-PUMA-1M data] :large_blue_circle:
  • VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search, arXiv:2503.10582 [paper] [VisualWebInstruct data] :large_blue_circle:
  • MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [data] [MAVIS-Instruct data]
  • Omni-MATH: A Universal Olympiad Level Mathematic Benchmark for Large Language Models, ICLR 2025 [paper] [Omni-MATH data] :large_blue_circle:
  • MathConstruct: Challenging LLM Reasoning with Constructive Proofs, ICLR 2025 VerifAI Workshop [paper] [MathConstruct data] :large_blue_circle:
  • Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency, arXiv:2504.18589 [paper] [VCBench data] :large_blue_circle:
  • Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models, arXiv:2503.21380 [paper] [OlymMATH data] :large_blue_circle:
  • Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?, arXiv:2504.00509 [paper] [RoR-Bench data] :large_blue_circle:
  • PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts, arXiv:2504.18428 [paper] [PolyMath data] :large_blue_circle:
  • LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs, NAACL 2025 [paper] [MaTT data] :large_blue_circle:
  • Who's the MVP? A Game-Theoretic Evaluation Benchmark for Modular Attribution in LLM Agents, arXiv:2502.00510 [paper] [CapaBench data] :large_blue_circle:
  • MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations, ICLR 2025 LLM Reason&Plan Workshop [paper] [MATH-Perturb data] :large_blue_circle:
  • Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning, arXiv:2504.09772 [paper] [M500 data] :large_blue_circle:
  • Key-Point-Driven Data Synthesis with Its Enhancement on Mathematical Reasoning, AAAI 2025 [paper] [KPMATH-M data] :large_blue_circle:
  • MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems, arXiv:2503.16549 [paper] [FlowVerse data] :large_blue_circle:

Tasks and Datasets - Other Geometry Tasks

Geometric Diagram Generation

  • GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper] [GeoX-pretrain data]
  • Automatic Reconstruction of Plane Geometry Figures in Documents, EITT 2015 [paper] :small_red_triangle: :x:
  • Solid Geometric Object Reconstruction from Single Line Drawing Image, GRAPP 2015 [paper] :small_red_triangle: :x:
  • Recovering Solid Geometric Object from Single Line Drawing Image, Multimed Tools Appl 2016 [paper] :small_red_triangle: :x:
  • An Example-based Approach to 3D Man-made Object Reconstruction from Line Drawings, Pattern Recogn 2016 [paper] :small_red_triangle: :x:
  • Context-aware Geometric Object Reconstruction for Mobile Education, MM 2016 [paper] :small_red_triangle: :x:
  • Automated Generation of Illustrations for Synthetic Geometry Proofs, ADG 2021 [paper] :small_red_triangle: :x:
  • Automatically Building Diagrams for Olympiad Geometry Problems, CADE 2021 [paper] [GMBL data] :small_red_triangle: :x:
  • A Precise Text-to-Diagram Generation Method for Elementary Geometry, ICCWAMTIP 2023 [paper] :small_red_triangle:
  • MagicGeo: Training-Free Text-Guided Geometric Diagram Generation, arXiv:2502.13855 [paper] [MagicGeoBench data] :small_red_triangle:
  • GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions, arXiv:2504.10146 [paper]

Geometric Construction Problem

  • Learning to Solve Geometric Construction Problems from Images, CICM 2021 [paper] :small_red_triangle:
  • EuclidNet: Deep Visual Reasoning for Constructible Problems in Geometry, AIML 2023 [paper] :small_red_triangle:
  • Beyond Lines and Circles Unveiling the Geometric Reasoning Gap in Large Language Models, Findings of EMNLP 2024 [paper] [Euclidea/PyEuclidea data] :small_red_triangle:

Geometric Figure Retrieval

  • Plane Geometry Figure Retrieval Based on Bilayer Geometric Attributed Graph Matching, ICPR 2014 [paper] :small_red_triangle: :x:
  • Plane Geometry Figure Retrieval with Bag of Shapes, IAPR 2014 DAS Workshop [paper] :small_red_triangle: :x:
  • Plane Geometry Diagram Retrieval by Using Hierarchical Searching Strategy, ICIMCS 2016 [paper] :small_red_triangle: :x:
  • Analysis of Stroke Intersection for Overlapping PGF Elements, IAPR 2016 DAS Workshop [paper] :small_red_triangle: :x:
  • Improving PGF retrieval effectiveness with active learning, ICPR 2016 [paper] :small_red_triangle: :x:
  • Improving Retrieval of Plane Geometry Figure with Learning to Rank, PTRL 2016 [paper] :small_red_triangle: :x:

Geometric Autoformalization

Methods - Architectures

Encoder-Decoder

  • Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning, ACL 2021 [paper]
  • GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning, Findings of ACL 2021 [paper]
  • Sequence to General Tree Knowledge-Guided Geometry Word Problem Solving, ACL-IJCNLP 2021 [paper]
  • A Graph Convolutional Network Feature Learning Framework for Interpretable Geometry Problem Solving, IEIR 2022 [paper]
  • An Augmented Benchmark Dataset for Geometric Question Answering through Dual Parallel Text Encoding, COLING 2022 [paper]
  • UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression, EMNLP 2022 [paper]
  • Solving Geometry Problems via Feature Learning and Contrastive Learning of Multimodal Data, CMES 2023 [paper]
  • A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram, IJCAI 2023 [paper]
  • UniMath: A Foundational and Multimodal Mathematical Reasoner, EMNLP 2023 [paper] :large_blue_circle:
  • Interpretable Geometry Problem Solving Using Improved RetinaNet and Graph Convolutional Network, Electronics 2023 [paper]
  • A Symbolic Characters Aware Model for Solving Geometry Problems, MM 2023 [paper]
  • The Geometric Neural Solution Combined with Text Diagram Parsing, IEIR 2023 [paper]
  • SUFFI-GPSC: Sufficient Geometry Problem Solution Checking with Symbolic Computation and Logical Reasoning, ICCWAMTIP 2023 [paper]
  • LANS: A Layout-Aware Neural Solver for Plane Geometry Problem, Findings of ACL 2024 [paper]
  • GAPS: Geometry-Aware Problem Solver, arXiv:2401.16287 [paper]
  • E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator, CVPR 2024 [paper]
  • FGeo-TP: A Language Model-Enhanced Solver for Geometry Problems, Symmetry 2024 [paper]
  • FGeo-DRL: Deductive Reasoning for Geometric Problems Through Deep Reinforcement Learning, Symmetry 2024 [paper]
  • FGeo-HyperGNet: Geometric Problem Solving Integrating Formal Symbolic System and Hypergraph Neural Network, arXiv:2402.11461 [paper]
  • GOLD: Geometry Problem Solver With Natural Language Description, Findings of NAACL 2024 [paper]
  • Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process, IJCAI 2024 [paper]
  • Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models, EMNLP Findings 2024 [paper] :large_blue_circle:
  • Fuse, Reason and Verify: Geometry Problem Solving With Parsed Clauses From Diagram, arXiv:2407.07327 [paper]
  • EAGLE: Elevating Geometric Reasoning Through LLM-Empowered Visual Instruction Tuning, arXiv:2408.11397 [paper]
  • MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models, arXiv:2409.00147 [paper] :large_blue_circle:
  • MathGLM-Vision: Solving Mathematical Problems With Multi-Modal Large Language Model, arXiv:2409.13729 [paper] :large_blue_circle:
  • Enhancing Geometry Problem Solving With Attention Mechanism and Super-Resolution, ICBASE 2024 [paper]
  • Geo-Qwen: A Geometry Problem-Solving Method Based on Generative Large Language Models and Heuristic Reasoning, ICCWAMTIP 2024 [paper]
  • Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems With Meta In-Context Learning, LGM3A 2024 [paper]
  • A Geometric Neural Solving Method Based on a Diagram Text Information Fusion Analysis, Sci. Rep. 2024 [paper]
  • Maths: Multimodal Transformer-Based Human-Readable Solver, ICME 2024 [paper]
  • R-CoT: Reverse Chain-of-Thought Problem Generation for Geometric Reasoning in Large Multimodal Models, arXiv:2410.17885 [paper]
  • SANS: Spatial-Aware Neural Solver for Plane Geometry Problem, ICPR 2024 [paper]
  • G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model, ICLR 2025 [paper]
  • MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [paper]
  • GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper]
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper]
  • GeoDANO: Geometric VLM with Domain Agnostic Vision Encoder, arXiv:2502.11360 [paper]
  • Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning, AAAI 2025 [paper] :large_blue_circle:
  • GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models, Findings of NAACL 2025 [paper]
  • VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search, arXiv:2503.10582 [paper] [VisualWebInstruct data] :large_blue_circle:
  • GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs, AAAI 2025 [paper]
  • Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration, arXiv:2504.12773 [paper]
  • RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?, arXiv:2501.11284 [paper]
  • Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs, arXiv:2501.06430 [paper]
  • LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL, arXiv:2503.07536 [paper]

Other Architectures

  • Geometry Problem Solving Based on Counter-factual Evolutionary Reasoning, CASE 2023 [paper]
  • GeoDRL: A Self-Learning Framework for Geometry Problem Solving using Reinforcement Learning in Deductive Reasoning, ACL 2023 [paper]
  • Hologram Reasoning for Solving Algebra Problems With Geometry Diagrams, arXiv:2408.10592 [paper]
  • Solving Olympiad Geometry Without Human Demonstrations, Nature 2024 [paper]
  • Wu’s Method Boosts Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry, NeurIPS 2024 MATH-AI Workshop [paper]
  • Proposing and Solving Olympiad Geometry with Guided Tree Search, arXiv:2412.10673 [paper]
  • Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2, arXiv:2502.03544 [paper]
  • DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving, NeurIPS 2024 [paper] :large_blue_circle:
  • MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning, arXiv:2412.12609 [paper] :large_blue_circle:
  • MathScale: Scaling Instruction Tuning for Mathematical Reasoning, ICML 2024 [paper] :large_blue_circle:
  • System-2 Mathematical Reasoning via Enriched Instruction Tuning, arXiv:2412.16964 [paper] :large_blue_circle:
  • Pi-GPS: Enhancing Geometry Problem Solving by Unleashing the Power of Diagrammatic Information, arXiv:2503.05543 [paper]
  • GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions, arXiv:2504.10146 [paper]
  • Offline Training of Language Model Agents with Functions as Learnable Weights, ICML 2024 [paper] :large_blue_circle:
  • Strategyllm: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving, NeurIPS 2024 [paper] :large_blue_circle:
  • MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems, NeurIPS 2024 [paper] :large_blue_circle:
  • Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate, ICLR 2025 [paper] :large_blue_circle:

Methods - Training Stage

Pre-Training

  • GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning, Findings of ACL 2021 [paper]
  • UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression, EMNLP 2022 [paper]
  • A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram, IJCAI 2023 [paper]
  • Fuse, Reason and Verify: Geometry Problem Solving With Parsed Clauses From Diagram, arXiv:2407.07327 [paper]
  • A Symbolic Characters Aware Model for Solving Geometry Problems, MM 2023 [paper]
  • LANS: A Layout-Aware Neural Solver for Plane Geometry Problem, Findings of ACL 2024 [paper]
  • A Geometric Neural Solving Method Based on a Diagram Text Information Fusion Analysis, Sci. Rep. 2024 [paper]
  • SANS: Spatial-Aware Neural Solver for Plane Geometry Problem, ICPR 2024 [paper]
  • Measuring Mathematical Problem Solving With the MATH Dataset, NeurIPS 2021 [paper] :large_blue_circle:
  • InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper]
  • GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper]
  • MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [data]
  • GeoDANO: Geometric VLM with Domain Agnostic Vision Encoder, arXiv:2502.11360 [paper]
  • Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs, arXiv:2501.06430 [paper]

Supervised Fine-Tuning

  • Synthetic Data Generator for Solving Korean Arithmetic Word Problem, Mathematics 2022 [paper] :large_blue_circle:
  • GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning, ICML 2024 AI4MATH Workshop [paper]
  • MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [paper]
  • Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration, arXiv:2504.12773 [paper]
  • TrustGeoGen: Scalable and Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving, arXiv:2504.15780 [paper]
  • MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams, arXiv:2503.20745 [paper] [MATHGLANCE/GeoPeP data]
  • Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding, Findings of ACL 2025 [paper] [CogAlign-Probing/CogAlign-train data]
  • VisOnlyQA: Large Vision Language Models Still Struggle With Visual Perception of Geometric Information, arXiv:2412.00947 [paper] :large_blue_circle:
  • MathScale: Scaling Instruction Tuning for Mathematical Reasoning, ICML 2024 [paper] :large_blue_circle:
  • Key-Point-Driven Data Synthesis with Its Enhancement on Mathematical Reasoning, AAAI 2025 [paper] :large_blue_circle:
  • R-CoT: Reverse Chain-of-Thought Problem Generation for Geometric Reasoning in Large Multimodal Models, arXiv:2410.17885 [paper]
  • VISTA: Visual Integrated System for Tailored Automation in Math Problem Generation Using LLM, PMLR 2025 [paper]
  • Feynman: Knowledge-Infused Diagramming Agent for Scaling Visual Reasoning Data, openreview 2025 [paper] :large_blue_circle:
  • Proposing and Solving Olympiad Geometry with Guided Tree Search, arXiv:2412.10673 [paper]
  • An Augmented Benchmark Dataset for Geometric Question Answering through Dual Parallel Text Encoding, COLING 2022 [paper]
  • A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram, IJCAI 2023 [paper]
  • GAPS: Geometry-Aware Problem Solver, arXiv:2401.16287 [paper]
  • E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator, CVPR 2024 [paper]
  • FormalGeo: An Extensible Formalized Framework for Olympiad Geometric Problem Solving, arXiv:2310.18021 [paper] :x:
  • A Deep Reinforcement Learning Agent for Geometry Online Tutoring, KAIS 2023 [paper]
  • SANS: Spatial-Aware Neural Solver for Plane Geometry Problem, ICPR 2024 [paper]
  • DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving, NeurIPS 2024 [paper] :large_blue_circle:
  • Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models, EMNLP Findings 2024 [paper] [MathV360K data] :large_blue_circle:
  • GeoVQA: A Comprehensive Multimodal Geometry Dataset for Secondary Education, MIPR 2024 [paper]
  • Advancing Multimodal LLMs: A Focus on Geometry Problem Solving Reasoning and Sequential Scoring, MMASIA 2024 [paper]
  • Vision-Language Models Can Self-Improve Reasoning via Reflection, arXiv:2411.00855 [paper] :large_blue_circle:
  • MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning, arXiv:2412.12609 [paper] :large_blue_circle:
  • System-2 Mathematical Reasoning via Enriched Instruction Tuning, arXiv:2412.16964 [paper] :large_blue_circle:
  • MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification, arXiv:2502.13383 [paper] :large_blue_circle:
  • G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model, ICLR 2025 [paper]
  • GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models, Findings of NAACL 2025 [paper]
  • M3CoT: A Novel Benchmark for Multi-Domain Multi-Step Multi-Modal Chain-of-Thought, ACL 2024 [paper] :large_blue_circle:
  • URSA: Understanding and Verifying Chain-of-Thought Reasoning in Multimodal Mathematics, arXiv:2501.04686 [paper] :large_blue_circle:
  • GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs, AAAI 2025 [paper]
  • LLaVA-o1: Let Vision Language Models Reason Step-by-Step, arXiv:2411.10440 [paper] :large_blue_circle:
  • AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning, arXiv:2411.11930 [paper] :large_blue_circle:
  • RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?, arXiv:2501.11284 [paper]
  • Virgo: A Preliminary Exploration on Reproducing o1-like MLLM, arXiv:2501.01904 [paper] :large_blue_circle:
  • BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models, Findings of ACL 2024 [paper]
  • GeoGPT4V: Towards Geometric Multi-Modal Large Language Models With Geometric Image Generation, EMNLP 2024 [paper]
  • Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper]
  • GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper]
  • SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement, arXiv:2504.07934 [paper] :large_blue_circle:
  • VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search, arXiv:2503.10582 [paper] :large_blue_circle:

Reinforcement Learning

  • A Deep Reinforcement Learning Agent for Geometry Online Tutoring, KAIS 2023 [paper]
  • GeoDRL: A Self-Learning Framework for Geometry Problem Solving using Reinforcement Learning in Deductive Reasoning, ACL 2023 [paper]
  • FGeo-DRL: Deductive Reasoning for Geometric Problems Through Deep Reinforcement Learning, Symmetry 2024 [paper]
  • Hologram Reasoning for Solving Algebra Problems With Geometry Diagrams, arXiv:2408.10592 [paper]
  • LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL, arXiv:2503.07536 [paper]
  • MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models, arXiv:2409.00147 [paper] :large_blue_circle:
  • MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [paper]
  • RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?, arXiv:2501.11284 [paper]
  • Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding, Findings of ACL 2025 [paper]
  • Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models, arXiv:2503.06749 [paper] :large_blue_circle:
  • OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement, arXiv:2503.17352 [paper] :large_blue_circle:
  • Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning, arXiv:2503.20752 [paper] :large_blue_circle:
  • Boosting the Generalization and Reasoning of Vision Language Models with Curriculum Reinforcement Learning, arXiv:2503.07065 [paper] :large_blue_circle:
  • GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions, arXiv:2504.10146 [paper]
  • Boosting MLLM Reasoning with Text-Debiased Hint-GRPO, arXiv:2503.23905 [paper]
  • SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models, arXiv:2504.11468 [paper] :large_blue_circle:
  • NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation, arXiv:2504.13055 [paper] :large_blue_circle:
  • Reinforcement Learning for Reasoning in Large Language Models with One Training Example, arXiv:2504.20571 [paper] :large_blue_circle:
  • GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning, arXiv:2504.02546 [paper]

Methods - Inference Stage

Test-Time Scaling

  • Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling, ICML 2024 [paper] :large_blue_circle:
  • Hint-before-Solving Prompting: Guiding LLMs to Effectively Utilize Encoded Knowledge, arXiv:2402.14310 [paper] :large_blue_circle:
  • Null-Shot Prompting: Rethinking Prompting Large Language Models With Hallucination, EMNLP 2024 [paper] :large_blue_circle:
  • Cumulative Reasoning with Large Language Models, arXiv:2308.04371 [paper] :large_blue_circle:
  • Progressive-Hint Prompting Improves Reasoning in Large Language Models, ICML 2024 AI4MATH Workshop [paper] :large_blue_circle:
  • MathSensei: Mathematical Reasoning with a Tool-Augmented Large Language Model, ICLR 2024 ME-FoMo Workshop [paper] :large_blue_circle:
  • Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation, NeurIPS 2024 [paper] :large_blue_circle:
  • SBSC: Step-By-Step Coding for Improving Mathematical Olympiad Performance, ICLR 2025 [paper] :large_blue_circle:
  • Reason-and-Execute Prompting: Enhancing Multi-Modal Large Language Models for Solving Geometry Questions, MM 2024 [paper]
  • Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts, EMNLP 2023 [paper] :large_blue_circle:
  • CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models, Findings of EMNLP 2023 [paper] :large_blue_circle:
  • ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving, ICLR 2024 [paper] :large_blue_circle:
  • Evaluating Automated Geometric Problem Solving With Formal Language Generation on Large Multimodal Models, IEIR 2024 [paper]
  • Describe-then-Reason: Improving Multimodal Mathematical Reasoning Through Visual Comprehension Training, arXiv:2404.14604 [paper] :large_blue_circle:
  • Beyond Captioning: Task-Specific Prompting for Improved VLM Performance in Mathematical Reasoning, arXiv:2410.05928 [paper]
  • Multi-Step Chain-of-Thought in Geometry Problem Solving, EIECS 2024 [paper]
  • Proposing and Solving Olympiad Geometry with Guided Tree Search, arXiv:2412.10673 [paper]
  • Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration, arXiv:2504.12773 [paper]
  • Solving Olympiad Geometry Without Human Demonstrations, Nature 2024 [paper]
  • Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2, arXiv:2502.03544 [paper]
  • GeoDRL: A Self-Learning Framework for Geometry Problem Solving using Reinforcement Learning in Deductive Reasoning, ACL 2023 [paper]
  • GAPS: Geometry-Aware Problem Solver, arXiv:2401.16287 [paper]
  • LLaVA-o1: Let Vision Language Models Reason Step-by-Step, arXiv:2411.10440 [paper] :large_blue_circle:
  • FGeo-DRL: Deductive Reasoning for Geometric Problems Through Deep Reinforcement Learning, Symmetry 2024 [paper]
  • MC-NEST--Enhancing Mathematical Reasoning in Large Language Models with a Monte Carlo Nash Equilibrium Self-Refine Tree, arXiv:2411.15645 [paper] :large_blue_circle:
  • Mulberry: Empowering MLLM With o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search, arXiv:2412.18319 [paper] :large_blue_circle:
  • Progressive Multimodal Reasoning via Active Retrieval, arXiv:2412.14835 [paper] :large_blue_circle:
  • Boosting Multimodal Reasoning with MCTS-Automated Structured Thinking, arXiv:2502.02339 [paper] :large_blue_circle:
  • VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search, arXiv:2504.09130 [paper]
  • Deliberate Reasoning for LLMs as Structure-Aware Planning with Accurate World Model, arXiv:2410.03136 [paper] :large_blue_circle:
  • AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning, arXiv:2411.11930 [paper] :large_blue_circle:
  • Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?, arXiv:2503.06252 [paper] :large_blue_circle:
  • URSA: Understanding and Verifying Chain-of-Thought Reasoning in Multimodal Mathematics, arXiv:2501.04686 [paper] :large_blue_circle:
  • VisualPRM: An Effective Process Reward Model for Multimodal Reasoning, arXiv:2503.10291 [paper] :large_blue_circle:
  • VILBENCH: A Suite for Vision-Language Process Reward Modeling, arXiv:2503.20271 [paper] :large_blue_circle:
  • PRM-BAS: Enhancing Multimodal Reasoning through PRM-guided Beam Annealing Search, arXiv:2504.10222 [paper] :large_blue_circle:
  • Learning From Correctness Without Prompting Makes LLM Efficient Reasoner, COLM 2024 [paper] :large_blue_circle:
  • Generative Verifiers: Reward Modeling as Next-Token Prediction, ICLR 2025 [paper] :large_blue_circle:
  • Vision-Language Models Can Self-Improve Reasoning via Reflection, arXiv:2411.00855 [paper] :large_blue_circle:
  • Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning, arXiv:2504.09772 [paper] :large_blue_circle:

Knowledge-Augmented Inference

  • Give me a Hint: Can LLMs Take a Hint to Solve Math Problems?, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  • Skills-in-Context: Unlocking Compositionality in Large Language Models, Findings of EMNLP 2024 [paper] :large_blue_circle:
  • Curriculum Demonstration Selection for In-Context Learning, SAC 2025 [paper] :large_blue_circle:
  • CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models, AAAI 2025 [paper] :large_blue_circle:
  • All in an Aggregated Image for In-Image Learning, arXiv:2402.17971 [paper] :large_blue_circle:
  • Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems With Meta In-Context Learning, LGM3A 2024 [paper]
  • Advancing Multimodal LLMs: A Focus on Geometry Problem Solving Reasoning and Sequential Scoring, MMASIA 2024 [paper]
  • GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models, Findings of NAACL 2025 [paper]
  • Enhancing LLM Reasoning via Vision-Augmented Prompting, NeurIPS 2024 [paper]
  • Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models, NeurIPS 2024 [paper] :large_blue_circle:
  • Interactive Sketchpad: A Multimodal Tutoring System for Collaborative, Visual Problem-Solving, arXiv:2503.16434 [paper] :large_blue_circle:
  • CogCom: A Visual Language Model with Chain-of-Manipulations Reasoning, ICLR 2025 [paper] :large_blue_circle:
  • VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search, arXiv:2504.09130 [paper]
  • Learning to Plan by Updating Natural Language, Findings of EMNLP 2024 [paper] :large_blue_circle:
  • Explicit Memory Learning with Expectation Maximization, EMNLP 2024 [paper] :large_blue_circle:
  • The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers, TPAMI 2019 [paper] :large_blue_circle: :x:
  • Deep Learning in Automatic Math Word Problem Solvers, AI in Learning: Designing the Future 2022 [article] :large_blue_circle:
  • Evolution of Automated Deduction and Dynamic Constructions in Geometry, Mathematics Education in the Age of Artificial Intelligence: How Artificial Intelligence can Serve Mathematical Human Learning 2022 [article] :x:
  • A Survey of Deep Learning for Mathematical Reasoning, ACL 2023 [paper] :large_blue_circle:
  • Systematic Literature Review: Application of Dynamic Geometry Software to Improve Mathematical Problem-Solving Skills, Mathline: Jurnal Matematika Dan Pendidikan Matematika 2023 [paper] :x:
  • A Survey of Reasoning with Foundation Models, arXiv:2312.11562 [paper] :large_blue_circle:
  • A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook, ACM Comput. Surv. 2023 [paper] :large_blue_circle:
  • Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges, arXiv:2401.08664 [paper] :large_blue_circle:
  • Large Language Models for Mathematical Reasoning: Progresses and Challenges, EACL 2024 [paper] :large_blue_circle:
  • A Survey on Deep Learning for Theorem Proving, COLM 2024 [paper] :large_blue_circle:
  • A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery, EMNLP 2024 [paper] :large_blue_circle:
  • Towards Robust Automated Math Problem Solving: A Survey of Statistical and Deep Learning Approaches, Evol. Intell. 2024 [paper] :large_blue_circle:
  • A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges, Findings of ACL 2025 [paper] :large_blue_circle:
  • Decoding Math: A Review of Datasets Shaping AI-Driven Mathematical Reasoning, JIM 2025 [paper] :large_blue_circle:
  • Visual Large Language Models for Generalized and Specialized Application, arXiv:2501.02765 [paper] :large_blue_circle:
  • From System 1 to System 2: A Survey of Reasoning Large Language Models, arXiv:2502.17419 [paper] :large_blue_circle:
  • Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents, arXiv:2503.24047 [paper] :large_blue_circle:

Years

2014

  1. Diagram Understanding in Geometry Questions, AAAI 2014 [paper] :x:
  2. Synthesis of Geometry Proof Problems, AAAI 2014 [paper] :x:
  3. Plane Geometry Figure Retrieval Based on Bilayer Geometric Attributed Graph Matching, ICPR 2014 [paper] :small_red_triangle: :x:
  4. Plane Geometry Figure Retrieval with Bag of Shapes, IAPR 2014 DAS Workshop [paper] :small_red_triangle: :x:

2015

  1. Solving Geometry Problems: Combining Text and Diagram Interpretation, EMNLP 2015 [paper] :x:
  2. Automatic Reconstruction of Plane Geometry Figures in Documents, EITT 2015 [paper] :small_red_triangle: :x:
  3. Overlapped-Triangle Analysis with Hierarchical Ranking of Dominance, ICDAR 2015 [paper] :x:
  4. Solid Geometric Object Reconstruction from Single Line Drawing Image, GRAPP 2015 [paper] :small_red_triangle: :x:

2016

  1. Plane Geometry Diagram Retrieval by Using Hierarchical Searching Strategy, ICIMCS 2016 [paper] :small_red_triangle: :x:
  2. Analysis of Stroke Intersection for Overlapping PGF Elements, IAPR 2016 DAS Workshop [paper] :small_red_triangle: :x:
  3. AnalyticalInk: An Interactive Learning Environment for Math Word Problem Solving, IUI 2016 [paper] :x:
  4. My Computer Is an Honor Student — but How Intelligent Is It? Standardized Tests as a Measure of AI, AIMA 2016 [paper] :large_blue_circle: :x:
  5. Improving PGF retrieval effectiveness with active learning, ICPR 2016 [paper] :small_red_triangle: :x:
  6. Improving Retrieval of Plane Geometry Figure with Learning to Rank, PTRL 2016 [paper] :small_red_triangle: :x:
  7. Recovering Solid Geometric Object from Single Line Drawing Image, Multimed Tools Appl 2016 [paper] :small_red_triangle: :x:
  8. An Example-based Approach to 3D Man-made Object Reconstruction from Line Drawings, Pattern Recogn 2016 [paper] :small_red_triangle: :x:
  9. Context-aware Geometric Object Reconstruction for Mobile Education, MM 2016 [paper] :small_red_triangle: :x:

2017

  1. Semantic Parsing of Pre-University Math Problems, ACL 2017 [paper] :x:
  2. Synthesis of Solutions for Shaded Area Geometry Problems, FLAIRS 2017 [paper] :x:
  3. From Textbooks to Knowledge: A Case Study in Harvesting Axiomatic Knowledge from Textbooks to Solve Geometry Problems, EMNLP 2017 [paper] :x:
  4. Learning to Solve Geometry Problems from Natural Language Demonstrations in Textbooks, *SEM 2017 [paper] :x:
  5. Understanding Explicit Arithmetic Word Problems and Explicit Plane Geometry Problems Using Syntax-Semantics Models, IALP 2017 [paper] :x:
  6. Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers, EMNLP 2017 [paper] :large_blue_circle: :x:
  7. Retrieving Geometric Information from Images: The Case of Hand-Drawn Diagrams, KDD 2017 [paper] :x:
  8. Understanding Plane Geometry Problems by Integrating Relations Extracted from Text and Diagram, PSIVT 2017 [paper] :x:
  9. Automatic Assessment of Student Answers for Geometric Theorem Proving Questions, MERCon 2017 [paper] :x:

2018

  1. Automatic Understanding and Formalization of Natural Language Geometry Problems Using Syntax-Semantics Models, IJICIC 2018 [paper] :x:
  2. Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples, ACL 2018 [paper]

2019

  1. A Sharing Framework for Solving Explicit Arithmetic Word Problems and Proving Plane Geometry Theorems, IJPRAI 2019 [paper] :x:
  2. Discourse in Multimedia: A Case Study in Extracting Geometry Knowledge from Textbooks, CL 2019 [paper] :x:
  3. Automatically Proving Plane Geometry Theorems Stated by Text and Diagram, IJPRAI 2019 [paper] :x:
  4. Automatic Understanding and Formalization of Plane Geometry Proving Problems in Natural Language: A Supervised Approach, IJAIT 2019 [paper] :x:
  5. A Neural Semantic Parser for Math Problems Incorporating Multi-Sentence Information, TALLIP 2019 [paper] :large_blue_circle:
  6. AiFu at SemEval-2019 Task 10: A Symbolic and Sub-symbolic Integrated System for SAT Math Question Answering, SemEval 2019 [paper] :large_blue_circle:
  7. Robot for Mathematics College Entrance Examination, ATCM 2019 [paper] :large_blue_circle:
  8. SemEval-2019 Task 10: Math Question Answering, SemEval 2019 [paper] :large_blue_circle:
  9. The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers, TPAMI 2019 [paper] :large_blue_circle: :x:
  10. ProblemSolver at SemEval-2019 Task 10: Sequence-to-Sequence Learning and Expression Trees, SemEval 2019 [paper] :large_blue_circle:

2020

  1. Two-step Memory Networks for Deep Semantic Parsing of Geometry Word Problems, SOFSEM 2020 [paper]
  2. A Novel Geometric Information Retrieval Tool for Images of Geometric Diagrams, ICISE-IE 2020 [paper]
  3. Applied Aspects of the Integrated Problem Solving System with Natural Language Interface, Inforino 2020 [paper] :x:
  4. Design an Intelligent Problem Solver in Geometry based on Knowledge Model of Relations, Engineering Letters 2020 [paper] :x:
  5. Ontology-Controlled Geometric Solver, RCAI 2020 [paper] :x:
  6. 2D Geometric Shapes Dataset – For Machine Learning and Pattern Recognition, Data in Brief 2020 [paper]

2021

  1. Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning, ACL 2021 [paper]
  2. GeoRE: A Relation Extraction Dataset for Chinese Geometry Problems, NeurIPS 2021 MATHAI4ED Workshop [paper]
  3. GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning, Findings of ACL 2021 [paper]
  4. Semantic Parsing of Geometry Statements Using Supervised Machine Learning on Synthetic Data, NatFoM 2021 CICM Workshop [paper]
  5. Learning to Solve Geometric Construction Problems from Images, CICM 2021 [paper] :small_red_triangle:
  6. Automated Generation of Illustrations for Synthetic Geometry Proofs, ADG 2021 [paper] :small_red_triangle: :x:
  7. Solving Solid Geometric Calculation Problems in Text, TALE 2021 [paper] :x:
  8. Automated Discovery of Geometrical Theorems in GeoGebra, ThEdu 2021 [paper] :x:
  9. Automatically Building Diagrams for Olympiad Geometry Problems, CADE 2021 [paper] :small_red_triangle: :x:
  10. Linguistic Processor Integration for Solving Planimetric Problems, IJCINI 2021 [paper] :x:
  11. A Paradigm of Diagram Understanding in Problem Solving, TALE 2021 [paper] :x:
  12. Sequence to General Tree Knowledge-Guided Geometry Word Problem Solving, ACL-IJCNLP 2021 [paper]
  13. Proving Geometric Problem by Adding Auxiliary Lines-Based on Hypothetical Test, AIET 2021 [paper] :x:
  14. Solving Shaded Area Problems by Constructing Equations, AIET 2021 [paper] :x:
  15. Cognitive Patterns for Semantic Presentation of Natural-Language Descriptions of Well-Formalizable Problems, RCAI 2021 [paper] :x:
  16. Measuring Mathematical Problem Solving With the MATH Dataset, NeurIPS 2021 [paper] :large_blue_circle:

2022

  1. A Graph Convolutional Network Feature Learning Framework for Interpretable Geometry Problem Solving, IEIR 2022 [paper]
  2. An Augmented Benchmark Dataset for Geometric Question Answering through Dual Parallel Text Encoding, COLING 2022 [paper]
  3. Plane Geometry Diagram Parsing, IJCAI 2022 [paper]
  4. Learning to Understand Plane Geometry Diagram, NeurIPS 2022 MATH-AI Workshop [paper]
  5. PGDP5K: A Diagram Parsing Dataset for Plane Geometry Problems, ICPR 2022 [paper]
  6. UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression, EMNLP 2022 [paper]
  7. A Novel Geometry Problem Understanding Method based on Uniform Vectorized Syntax-Semantics Model, IEIR 2022 [paper]
  8. Geoclidean: Few-Shot Generalization in Euclidean Geometry, NeurIPS 2022 [paper]
  9. A Method for Expanding Predicates and Rules in Automated Geometry Reasoning System, Mathematics 2022 [paper] :x:
  10. Research on Geometry Problem Text Understanding Based on Bidirectional LSTM-CRF, ICDH 2022 [paper]
  11. Synthetic Data Generator for Solving Korean Arithmetic Word Problem, Mathematics 2022 [paper] :large_blue_circle:
  12. Usage of Stacked Long Short-Term Memory for Recognition of 3D Analytic Geometry Elements, ICAART 2022 [paper]
  13. Complex Modeling of Inductive and Deductive Reasoning by the Example of a Planimetric Problem Solver, IITI 2022 [paper] :x:
  14. Natural Language Processing and Functioning Ontological Solver with Visualization in an Integrated System, IntelliSys 2022 [paper] :x:
  15. Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models, TMLR 2022 [paper] :large_blue_circle:
  16. Deep Learning in Automatic Math Word Problem Solvers, AI in Learning: Designing the Future 2022 [article] :large_blue_circle:
  17. Evolution of Automated Deduction and Dynamic Constructions in Geometry, Mathematics Education in the Age of Artificial Intelligence: How Artificial Intelligence can Serve Mathematical Human Learning 2022 [article] :x:
  18. Supervised Learning Use to Acquire Knowledge from 2D Analytic Geometry Problems, ACIIDS 2022 [paper] :x:
  19. NUMGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks, ACL 2022 [paper] :large_blue_circle:
  20. Lila: A Unified Benchmark for Mathematical Reasoning, EMNLP 2022 [paper] :large_blue_circle:

2023

  1. EuclidNet: Deep Visual Reasoning for Constructible Problems in Geometry, AIML 2023 [paper] :small_red_triangle:
  2. Solving Geometry Problems via Feature Learning and Contrastive Learning of Multimodal Data, CMES 2023 [paper]
  3. A Deep Reinforcement Learning Agent for Geometry Online Tutoring, KAIS 2023 [paper]
  4. GeoDRL: A Self-Learning Framework for Geometry Problem Solving using Reinforcement Learning in Deductive Reasoning, ACL 2023 [paper]
  5. Solving Algebraic Problems with Geometry Diagrams Using Syntax-Semantics Diagram Understanding, Computers, Materials & Continua 2023 [paper] :x:
  6. A Multi-Modal Neural Geometric Solver with Textual Clauses Parsed from Diagram, IJCAI 2023 [paper]
  7. UniMath: A Foundational and Multimodal Mathematical Reasoner, EMNLP 2023 [paper] :large_blue_circle:
  8. Geometry Problem Solving Based on Counter-factual Evolutionary Reasoning, CASE 2023 [paper]
  9. Interpretable Geometry Problem Solving Using Improved RetinaNet and Graph Convolutional Network, Electronics 2023 [paper]
  10. A Symbolic Characters Aware Model for Solving Geometry Problems, MM 2023 [paper]
  11. FormalGeo: An Extensible Formalized Framework for Olympiad Geometric Problem Solving, arXiv:2310.18021 [paper] :x:
  12. A Precise Text-to-Diagram Generation Method for Elementary Geometry, ICCWAMTIP 2023 [paper] :small_red_triangle:
  13. The Geometric Neural Solution Combined with Text Diagram Parsing, IEIR 2023 [paper]
  14. SUFFI-GPSC: Sufficient Geometry Problem Solution Checking with Symbolic Computation and Logical Reasoning, ICCWAMTIP 2023 [paper]
  15. Extracting structured information from the textual description of geometry word problems, NLPIR 2023 [paper] :x:
  16. Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset, Findings of EMNLP 2023 [paper]
  17. Automated Evaluation of Student Answers for Geometric Questions Based on the Theorem 'Angles on a Straight Line Add to 180±', SLAAI-ICAI 2023 [paper]
  18. Estimating Answer Strategies using Online Handwritten Data: A Study using Geometry Problems, ICETC 2023 [paper]
  19. It Ain’t Over: A Multi-Aspect Diverse Math Word Problem Dataset, EMNLP 2023 [paper] :large_blue_circle:
  20. Visual Amplification of Geometry Problems: A Method for Synchronized Highlighting in Text and Diagrams, IEIR 2023 [paper]
  21. Systematic Literature Review: Application of Dynamic Geometry Software to Improve Mathematical Problem-solving Skills, JMPM 2023 [paper] :x:
  22. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them, Findings of ACL 2023 [paper]
  23. M3exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models, NeurIPS 2023 [paper] :large_blue_circle:
  24. TheoremQA: A Theorem-driven Question Answering Dataset, EMNLP 2023 [paper] :large_blue_circle:
  25. CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models, Findings of EMNLP 2023 [paper] :large_blue_circle:
  26. Cumulative Reasoning with Large Language Models, arXiv:2308.04371 [paper] :large_blue_circle:
  27. Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts, EMNLP 2023 [paper] :large_blue_circle:
  28. Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges, arXiv:2401.08664 [paper] :large_blue_circle:
  29. A Survey of Deep Learning for Mathematical Reasoning, ACL 2023 [paper] :large_blue_circle:
  30. Systematic Literature Review: Application of Dynamic Geometry Software to Improve Mathematical Problem-Solving Skills, Mathline: Jurnal Matematika Dan Pendidikan Matematika 2023 [paper] :x:
  31. A Survey of Reasoning with Foundation Models, arXiv:2312.11562 [paper] :large_blue_circle:
  32. A Survey of Reasoning with Foundation Models: Concepts, Methodologies, and Outlook, ACM Comput. Surv. 2023 [paper] :large_blue_circle:
  33. Geometry Problem Solving Based on Deep Learning, CSMIS 2023 [paper]

2024

  1. LANS: A Layout-Aware Neural Solver for Plane Geometry Problem, Findings of ACL 2024 [paper]
  2. GeomVerse: A Systematic Evaluation of Large Models for Geometric Reasoning, ICML 2024 AI4MATH Workshop [paper]
  3. Solving Olympiad Geometry Without Human Demonstrations, Nature 2024 [paper]
  4. GAPS: Geometry-Aware Problem Solver, arXiv:2401.16287 [paper]
  5. E-GPS: Explainable Geometry Problem Solving via Top-Down Solver and Bottom-Up Generator, CVPR 2024 [paper]
  6. Beyond Lines and Circles Unveiling the Geometric Reasoning Gap in Large Language Models, Findings of EMNLP 2024 [paper] :small_red_triangle:
  7. FGeo-TP: A Language Model-Enhanced Solver for Geometry Problems, Symmetry 2024 [paper]
  8. FGeo-DRL: Deductive Reasoning for Geometric Problems Through Deep Reinforcement Learning, Symmetry 2024 [paper]
  9. FGeo-SSS: A Search-Based Symbolic Solver for Human-Like Automated Geometric Reasoning, Symmetry 2024 [paper] :x:
  10. FGeo-HyperGNet: Geometric Problem Solving Integrating Formal Symbolic System and Hypergraph Neural Network, arXiv:2402.11461 [paper]
  11. OlympiadBench: A Challenging Benchmark for Promoting AGI With Olympiad-Level Bilingual Multimodal Scientific Problems, ACL 2024 [paper] :large_blue_circle:
  12. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts, ICLR 2024 [paper] :large_blue_circle:
  13. MathVerse: Does Your Multi-Modal LLM Truly See the Diagrams in Visual Math Problems?, ECCV 2024 [paper] :large_blue_circle:
  14. Measuring Multimodal Mathematical Reasoning With MATH-Vision Dataset, NeurIPS 2024 [paper] :large_blue_circle:
  15. MM-MATH: Advancing Multimodal Math Evaluation With Process Evaluation and Fine-Grained Classification, Findings of EMNLP 2024 [paper] :large_blue_circle:
  16. Wu’s Method Boosts Symbolic AI to Rival Silver Medalists and AlphaGeometry to Outperform Gold Medalists at IMO Geometry, NeurIPS 2024 MATH-AI Workshop [paper]
  17. GOLD: Geometry Problem Solver With Natural Language Description, Findings of NAACL 2024 [paper]
  18. Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process, IJCAI 2024 [paper]
  19. Autoformalizing Euclidean Geometry, ICML 2024 [paper] :small_red_triangle:
  20. GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving, Findings of ACL 2024 [paper]
  21. GeoGPT4V: Towards Geometric Multi-Modal Large Language Models With Geometric Image Generation, EMNLP 2024 [paper]
  22. Figuring Figures: An Assessment of Large Language Models on Different Modalities of Math Word Problems, ICMLT 2024 [paper]
  23. Math-LLaVA: Bootstrapping Mathematical Reasoning for Multimodal Large Language Models, EMNLP Findings 2024 [paper] :large_blue_circle:
  24. We-Math: Does Your Large Multimodal Model Achieve Human-Like Mathematical Reasoning?, arXiv:2407.01284 [paper] :large_blue_circle:
  25. Fuse, Reason and Verify: Geometry Problem Solving With Parsed Clauses From Diagram, arXiv:2407.07327 [paper]
  26. Is Your Model Really a Good Math Reasoner? Evaluating Mathematical Reasoning With Checklist, arXiv:2407.08733 [paper]
  27. Hologram Reasoning for Solving Algebra Problems With Geometry Diagrams, arXiv:2408.10592 [paper]
  28. EAGLE: Elevating Geometric Reasoning Through LLM-Empowered Visual Instruction Tuning, arXiv:2408.11397 [paper]
  29. Tangram: A Challenging Benchmark for Geometric Element Recognizing, arXiv:2408.13854 [paper]
  30. Leveraging Two-Level Deep Learning Classifers for 2D Shape Recognition to Automatically Solve Geometry Math Word Problems, PAA 2024 [paper]
  31. MultiMath: Bridging Visual and Mathematical Reasoning for Large Language Models, arXiv:2409.00147 [paper] :large_blue_circle:
  32. InfiMM-WebMath-40B: Advancing Multimodal Pre-Training for Enhanced Mathematical Reasoning, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  33. MathGLM-Vision: Solving Mathematical Problems With Multi-Modal Large Language Model, arXiv:2409.13729 [paper] :large_blue_circle:
  34. Enhancing Geometry Problem Solving With Attention Mechanism and Super-Resolution, ICBASE 2024 [paper]
  35. Automated Generation of Geometry Proof Problems Based on Point Geometry Identity, Journal of Automated Reasoning 2024 [paper] :x:
  36. Geo-Qwen: A Geometry Problem-Solving Method Based on Generative Large Language Models and Heuristic Reasoning, ICCWAMTIP 2024 [paper]
  37. Formal Representation and Solution of Plane Geometric Problems, NeurIPS 2024 MATH-AI Workshop [paper]
  38. GeoVQA: A Comprehensive Multimodal Geometry Dataset for Secondary Education, MIPR 2024 [paper]
  39. Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems With Meta In-Context Learning, LGM3A 2024 [paper]
  40. Reason-and-Execute Prompting: Enhancing Multi-Modal Large Language Models for Solving Geometry Questions, MM 2024 [paper]
  41. R-CoT: Reverse Chain-of-Thought Problem Generation for Geometric Reasoning in Large Multimodal Models, arXiv:2410.17885 [paper]
  42. LLaVA-o1: Let Vision Language Models Reason Step-by-Step, arXiv:2411.10440 [paper] :large_blue_circle:
  43. Vision-Language Models Can Self-Improve Reasoning via Reflection, arXiv:2411.00855 [paper] :large_blue_circle:
  44. A Geometric Neural Solving Method Based on a Diagram Text Information Fusion Analysis, Sci. Rep. 2024 [paper]
  45. Slow Perception: Let's Perceive Geometric Figures Step-by-Step, arXiv:2412.20631 [paper]
  46. Maths: Multimodal Transformer-Based Human-Readable Solver, ICME 2024 [paper]
  47. Automatic Extraction of Structured Information from Elementary Level Geometry Questions into Logic Forms, Multimed Tools Appl 2024 [paper]
  48. Improving Multimodal LLMs Ability in Geometry Problem Solving, Reasoning, and Multistep Scoring, arXiv:2412.00846 [paper]
  49. Advancing Multimodal LLMs: A Focus on Geometry Problem Solving Reasoning and Sequential Scoring, MMASIA 2024 [paper]
  50. Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models, NeurIPS 2024 [paper] :large_blue_circle:
  51. 2D Shape Detection for Solving Geometry Word Problems, IETE J. Res. 2024 [paper] :x:
  52. VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning, arXiv:2410.22995 [paper] :large_blue_circle:
  53. Euclid: Supercharging Multimodal LLMs With Synthetic High-Fidelity Visual Descriptions, arXiv:2412.08737 [paper]
  54. AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning, arXiv:2411.11930 [paper] :large_blue_circle:
  55. Mulberry: Empowering MLLM With o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search, arXiv:2412.18319 [paper] :large_blue_circle:
  56. What is the True Performance of Large Multimodal Models in Visual Context-Based Mathematical Reasoning? An Analysis of Multiple Datasets and Future Research Directions, ICTC 2024 [paper]
  57. GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models, arXiv:2412.21036 [paper]
  58. DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  59. An Enhanced Relation-Flow Algorithm for Solving Number Line Problems, IEIR 2024 [paper] :x:
  60. Describe-then-Reason: Improving Multimodal Mathematical Reasoning Through Visual Comprehension Training, arXiv:2404.14604 [paper] :large_blue_circle:
  61. Enhancing LLM Reasoning via Vision-Augmented Prompting, NeurIPS 2024 [paper]
  62. Evaluating Automated Geometric Problem Solving With Formal Language Generation on Large Multimodal Models, IEIR 2024 [paper]
  63. Multi-Step Chain-of-Thought in Geometry Problem Solving, EIECS 2024 [paper]
  64. VisOnlyQA: Large Vision Language Models Still Struggle With Visual Perception of Geometric Information, arXiv:2412.00947 [paper] :large_blue_circle:
  65. CMM-Math: A Chinese Multimodal Math Dataset to Evaluate and Enhance the Mathematics Reasoning of Large Multimodal Models, arXiv:2409.02834 [paper] :large_blue_circle:
  66. All in an Aggregated Image for In-Image Learning, arXiv:2402.17971 [paper] :large_blue_circle:
  67. CurveML: A Benchmark for Evaluating and Training Learning-Based Methods of Classification, Recognition, and Fitting of Plane Curves, Visual Comput 2024 [paper]
  68. Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models, ACL 2024 [paper] :large_blue_circle:
  69. MathScape: Evaluating MLLMs in Multimodal Math Scenarios Through a Hierarchical Benchmark, arXiv:2408.07543 [paper] :large_blue_circle:
  70. VisScience: An Extensive Benchmark for Evaluating K12 Educational Multi-Modal Scientific Reasoning, arXiv:2409.13730 [paper] :large_blue_circle:
  71. Progressive Multimodal Reasoning via Active Retrieval, arXiv:2412.14835 [paper] :large_blue_circle:
  72. Decomposing Complex Visual Comprehension Into Atomic Visual Skills for Vision Language Models, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  73. ReMI: A Dataset for Reasoning With Multiple Images, NeurIPS 2024 [paper] :large_blue_circle:
  74. M3GIA: A Cognition-Inspired Multilingual and Multimodal General Intelligence Ability Benchmark, arXiv:2406.05343 [paper] :large_blue_circle:
  75. Mathematical Problem Solving in Arabic: Assessing Large Language Models, Procedia Comput. Sci. 2024 [paper] :large_blue_circle:
  76. M3CoT: A Novel Benchmark for Multi-Domain Multi-Step Multi-Modal Chain-of-Thought, ACL 2024 [paper] :large_blue_circle:
  77. MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data, arXiv:2406.18321 [paper] :large_blue_circle:
  78. PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical Competition, NeurIPS 2024 [paper] :large_blue_circle:
  79. From Blind Solvers to Logical Thinkers: Benchmarking LLMs’ Logical Integrity on Faulty Mathematical Problems, arXiv:2410.18921 [paper] :large_blue_circle:
  80. ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models, Findings of ACL 2024 [paper] :large_blue_circle:
  81. Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning Gap, arXiv:2402.19450 [paper] :large_blue_circle:
  82. MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark, Findings of ACL 2024 [paper] :large_blue_circle:
  83. HARP: A Challenging Human-Annotated Math Reasoning Benchmark, arXiv:2412.08819 [paper] :large_blue_circle:
  84. Progressive-Hint Prompting Improves Reasoning in Large Language Models, ICML 2024 AI4MATH Workshop [paper] :large_blue_circle:
  85. Learning to Plan by Updating Natural Language, Findings of EMNLP 2024 [paper] :large_blue_circle:
  86. Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling, ICML 2024 [paper] :large_blue_circle:
  87. Skills-in-Context: Unlocking Compositionality in Large Language Models, Findings of EMNLP 2024 [paper] :large_blue_circle:
  88. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving, ICLR 2024 [paper] :large_blue_circle:
  89. Can Generative AI Solve Geometry Problems? Strengths and Weaknesses of LLMs for Geometric Reasoning in Spanish, IJIMAI 2024 [paper]
  90. Explicit Memory Learning with Expectation Maximization, EMNLP 2024 [paper] :large_blue_circle:
  91. MathSensei: Mathematical Reasoning with a Tool-Augmented Large Language Model, ICLR 2024 ME-FoMo Workshop [paper] :large_blue_circle:
  92. Null-Shot Prompting: Rethinking Prompting Large Language Models With Hallucination, EMNLP 2024 [paper] :large_blue_circle:
  93. Strategyllm: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving, NeurIPS 2024 [paper] :large_blue_circle:
  94. BBA: Bi-Modal Behavioral Alignment for Reasoning with Large Vision-Language Models, Findings of ACL 2024 [paper]
  95. Hint-before-Solving Prompting: Guiding LLMs to Effectively Utilize Encoded Knowledge, arXiv:2402.14310 [paper] :large_blue_circle:
  96. MathScale: Scaling Instruction Tuning for Mathematical Reasoning, ICML 2024 [paper] :large_blue_circle:
  97. Learning From Correctness Without Prompting Makes LLM Efficient Reasoner, COLM 2024 [paper] :large_blue_circle:
  98. MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems, NeurIPS 2024 [paper] :large_blue_circle:
  99. Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation, NeurIPS 2024 [paper] :large_blue_circle:
  100. Deliberate Reasoning for LLMs as Structure-Aware Planning with Accurate World Model, arXiv:2410.03136 [paper] :large_blue_circle:
  101. Give me a Hint: Can LLMs Take a Hint to Solve Math Problems?, NeurIPS 2024 MATH-AI Workshop [paper] :large_blue_circle:
  102. MC-NEST--Enhancing Mathematical Reasoning in Large Language Models with a Monte Carlo Nash Equilibrium Self-Refine Tree, arXiv:2411.15645 [paper] :large_blue_circle:
  103. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-Solving, NeurIPS 2024 [paper] :large_blue_circle:
  104. Offline Training of Language Model Agents with Functions as Learnable Weights, ICML 2024 [paper] :large_blue_circle:
  105. UTMath: Math Evaluation with Unit Test via Reasoning-to-Coding Thoughts, arXiv:2411.07240 [paper] :large_blue_circle:
  106. MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning, arXiv:2412.12609 [paper] :large_blue_circle:
  107. System-2 Mathematical Reasoning via Enriched Instruction Tuning, arXiv:2412.16964 [paper] :large_blue_circle:
  108. Beyond Captioning: Task-Specific Prompting for Improved VLM Performance in Mathematical Reasoning, arXiv:2410.05928 [paper]
  109. Data for Mathematical Copilots: Better Ways of Presenting Proofs for Machine Learning, arXiv:2412.15184 [paper] :large_blue_circle:
  110. Adapting Large Language Models for Education: Foundational Capabilities, Potentials, and Challenges, arXiv:2401.08664 [paper] :large_blue_circle:
  111. Large Language Models for Mathematical Reasoning: Progresses and Challenges, EACL 2024 [paper] :large_blue_circle:
  112. A Survey on Deep Learning for Theorem Proving, COLM 2024 [paper] :large_blue_circle:
  113. A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery, EMNLP 2024 [paper] :large_blue_circle:
  114. Towards Robust Automated Math Problem Solving: A Survey of Statistical and Deep Learning Approaches, Evol. Intell. 2024 [paper] :large_blue_circle:
  115. Proposing and Solving Olympiad Geometry with Guided Tree Search, arXiv:2412.10673 [paper]
  116. SANS: Spatial-Aware Neural Solver for Plane Geometry Problem, ICPR 2024 [paper]

2025

  1. AutoGeo: Automating Geometric Image Dataset Creation for Enhanced Geometry Understanding, IEEE Trans. Multimedia 2025 [paper]
  2. G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model, ICLR 2025 [paper]
  3. MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine, ICLR 2025 [paper]
  4. DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models, ICLR 2025 [paper] :large_blue_circle:
  5. Do Large Language Models Truly Understand Geometric Structures?, ICLR 2025 [paper]
  6. GeoX: Geometric Problem Solving Through Unified Formalized Vision-Language Pre-Training, ICLR 2025 [paper]
  7. Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver, ICASSP 2025 [paper]
  8. A Knowledge and Semantic Fusion Method for Automatic Geometry Problem Understanding, Appl. Sci. 2025 [paper]
  9. ElementaryCQT: A New Dataset and Its Deep Learning Analysis for 2D Geometric Shape Recognition, SN Comput. Sci. 2025 [paper]
  10. Exploration of Formalization Techniques for Geometric Entities in Planar Geometry Proposition Texts, JAIP 2025 [paper]
  11. FGeo-Parser: Autoformalization and Solution of Plane Geometric Problems, Symmetry 2025 [paper]
  12. GeoDANO: Geometric VLM with Domain Agnostic Vision Encoder, arXiv:2502.11360 [paper]
  13. Math-PUMA: Progressive Upward Multimodal Alignment to Enhance Mathematical Reasoning, AAAI 2025 [paper] :large_blue_circle:
  14. Multimodal Large Language Models for High School Mathematical Reasoning: Impact of Input Modality and Artifacts, Authorea Preprints 2025 [paper] :large_blue_circle:
  15. URSA: Understanding and Verifying Chain-of-Thought Reasoning in Multimodal Mathematics, arXiv:2501.04686 [paper] :large_blue_circle:
  16. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models, arXiv:2503.06749 [paper] :large_blue_circle:
  17. VISTA: Visual Integrated System for Tailored Automation in Math Problem Generation Using LLM, PMLR 2025 [paper]
  18. LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL, arXiv:2503.07536 [paper]
  19. VisualPRM: An Effective Process Reward Model for Multimodal Reasoning, arXiv:2503.10291 [paper] :large_blue_circle:
  20. VisualWebInstruct: Scaling up Multimodal Instruction Data through Web Search, arXiv:2503.10582 [paper] :large_blue_circle:
  21. VisNumBench: Evaluating Number Sense of Multimodal Large Language Models, arXiv:2503.14939 [paper] :large_blue_circle:
  22. Interactive Sketchpad: A Multimodal Tutoring System for Collaborative, Visual Problem-Solving, arXiv:2503.16434 [paper] :large_blue_circle:
  23. OpenVLThinker: An Early Exploration to Complex Vision-Language Reasoning via Iterative Self-Improvement, arXiv:2503.17352 [paper] :large_blue_circle:
  24. MathAgent: Leveraging a Mixture-of-Math-Agent Framework for Real-World Multimodal Mathematical Error Detection, arXiv:2503.18132 [paper] :large_blue_circle:
  25. Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning, arXiv:2503.20752 [paper] :large_blue_circle:
  26. VILBENCH: A Suite for Vision-Language Process Reward Modeling, arXiv:2503.20271 [paper] :large_blue_circle:
  27. SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement, arXiv:2504.07934 [paper] :large_blue_circle:
  28. VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search, arXiv:2504.09130 [paper]
  29. GNS: Solving Plane Geometry Problems by Neural-Symbolic Reasoning with Multi-Modal LLMs, AAAI 2025 [paper]
  30. Enhancing the Geometric Problem-Solving Ability of Multimodal LLMs via Symbolic-Neural Integration, arXiv:2504.12773 [paper]
  31. GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning, arXiv:2504.12597 [paper]
  32. CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models, AAAI 2025 [paper] :large_blue_circle:
  33. Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2, arXiv:2502.03544 [paper]
  34. Feynman: Knowledge-Infused Diagramming Agent for Scaling Visual Reasoning Data, openreview 2025 [paper] :large_blue_circle:
  35. GeoUni: A Unified Model for Generating Geometry Diagrams, Problems and Problem Solutions, arXiv:2504.10146 [paper]
  36. MagicGeo: Training-Free Text-Guided Geometric Diagram Generation, arXiv:2502.13855 [paper] :small_red_triangle:
  37. MATHGLANCE: Multimodal Large Language Models Do Not Know Where to Look in Mathematical Diagrams, arXiv:2503.20745 [paper]
  38. Virgo: A Preliminary Exploration on Reproducing o1-like MLLM, arXiv:2501.01904 [paper] :large_blue_circle:
  39. Open Eyes, Then Reason: Fine-grained Visual Mathematical Understanding in MLLMs, arXiv:2501.06430 [paper]
  40. MV-MATH: Evaluating Multimodal Math Reasoning in Multi-Visual Contexts, arXiv:2502.20808 [paper] :large_blue_circle:
  41. Pi-GPS: Enhancing Geometry Problem Solving by Unleashing the Power of Diagrammatic Information, arXiv:2503.05543 [paper]
  42. MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems, arXiv:2503.16549 [paper] :large_blue_circle:
  43. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?, arXiv:2501.11284 [paper]
  44. Can Atomic Step Decomposition Enhance the Self-structured Reasoning of Multimodal Large Models?, arXiv:2503.06252 [paper] :large_blue_circle:
  45. GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models, Findings of NAACL 2025 [paper]
  46. DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students’ Hand-Drawn Math Images, NAACL 2025 [paper] :large_blue_circle:
  47. Benchmarking Multimodal Mathematical Reasoning with Explicit Visual Dependency, arXiv:2504.18589 [paper] :large_blue_circle:
  48. CogCom: A Visual Language Model with Chain-of-Manipulations Reasoning, ICLR 2025 [paper] :large_blue_circle:
  49. CMMaTH: A Chinese Multi-modal Math Skill Evaluation Benchmark for Foundation Models, COLING 2025 [paper] :large_blue_circle:
  50. Boosting Multimodal Reasoning with MCTS-Automated Structured Thinking, arXiv:2502.02339 [paper] :large_blue_circle:
  51. Forgotten Polygons: Multimodal Large Language Models are Shape-Blind, arXiv:2502.15969 [paper]
  52. Boosting the Generalization and Reasoning of Vision Language Models with Curriculum Reinforcement Learning, arXiv:2503.07065 [paper] :large_blue_circle:
  53. Boosting MLLM Reasoning with Text-Debiased Hint-GRPO, arXiv:2503.23905 [paper]
  54. PRM-BAS: Enhancing Multimodal Reasoning through PRM-guided Beam Annealing Search, arXiv:2504.10222 [paper] :large_blue_circle:
  55. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models, arXiv:2504.11468 [paper] :large_blue_circle:
  56. NoisyRollout: Reinforcing Visual Reasoning with Data Augmentation, arXiv:2504.13055 [paper] :large_blue_circle:
  57. TrustGeoGen: Scalable and Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving, arXiv:2504.15780 [paper]
  58. On The Potential of Using Generative Artificial Intelligence for Geometry Educational Activities, hal 2025 [paper]
  59. Omni-MATH: A Universal Olympiad Level Mathematic Benchmark for Large Language Models, ICLR 2025 [paper] :large_blue_circle:
  60. MathConstruct: Challenging LLM Reasoning with Constructive Proofs, ICLR 2025 VerifAI Workshop [paper] :large_blue_circle:
  61. TMATH: A Dataset for Evaluating Large Language Models in Generating Educational Hints for Math Word Problems, COLING 2025 [paper] :large_blue_circle:
  62. MathClean: A Benchmark for Synthetic Mathematical Data Cleaning, arXiv:2502.19508 [paper] :large_blue_circle:
  63. Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models, arXiv:2503.21380 [paper] :large_blue_circle:
  64. Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?, arXiv:2504.00509 [paper] :large_blue_circle:
  65. PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts, arXiv:2504.18428 [paper] :large_blue_circle:
  66. LLMs Are Not Intelligent Thinkers: Introducing Mathematical Topic Tree Benchmark for Comprehensive Evaluation of LLMs, NAACL 2025 [paper] :large_blue_circle:
  67. Who's the MVP? A Game-Theoretic Evaluation Benchmark for Modular Attribution in LLM Agents, arXiv:2502.00510 [paper] :large_blue_circle:
  68. MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations, ICLR 2025 LLM Reason&Plan Workshop [paper] :large_blue_circle:
  69. Generative Verifiers: Reward Modeling as Next-Token Prediction, ICLR 2025 [paper] :large_blue_circle:
  70. Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate, ICLR 2025 [paper] :large_blue_circle:
  71. SBSC: Step-By-Step Coding for Improving Mathematical Olympiad Performance, ICLR 2025 [paper] :large_blue_circle:
  72. Curriculum Demonstration Selection for In-Context Learning, SAC 2025 [paper] :large_blue_circle:
  73. GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning, arXiv:2504.02546 [paper]
  74. Reinforcement Learning for Reasoning in Large Language Models with One Training Example, arXiv:2504.20571 [paper] :large_blue_circle:
  75. Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding, Findings of ACL 2025 [paper]
  76. MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification, arXiv:2502.13383 [paper] :large_blue_circle:
  77. Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning, arXiv:2504.09772 [paper] :large_blue_circle:
  78. Climbing the Ladder of Reasoning: What LLMs Can-and Still Can't-Solve after SFT?, arXiv:2504.11741 [paper] :large_blue_circle:
  79. Key-Point-Driven Data Synthesis with Its Enhancement on Mathematical Reasoning, AAAI 2025 [paper] :large_blue_circle:
  80. A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges, Findings of ACL 2025 [paper] :large_blue_circle:
  81. Decoding Math: A Review of Datasets Shaping AI-Driven Mathematical Reasoning, JIM 2025 [paper] :large_blue_circle:
  82. Visual Large Language Models for Generalized and Specialized Application, arXiv:2501.02765 [paper] :large_blue_circle:
  83. From System 1 to System 2: A Survey of Reasoning Large Language Models, arXiv:2502.17419 [paper] :large_blue_circle:
  84. Towards Scientific Intelligence: A Survey of LLM-based Scientific Agents, arXiv:2503.24047 [paper] :large_blue_circle:
  85. Plane Geometry Problem Solving with Multi-modal Reasoning: A Survey, arXiv:2505.14340 [paper]
  86. Towards Geometry Problem Solving in the Large Model Era: A Survey, arXiv:2506.02690 [paper]

Citation

If you find this repository useful, please consider citing our survey paper:

@article{ma2025survey,
  title={A Survey of Deep Learning for Geometry Problem Solving},
  author={Ma, Jianzhe and Wang, Wenxuan and Jin, Qin},
  journal={arXiv preprint arXiv:2507.11936},
  year={2025}
}