Awesome LLM-Based Human-Agent Collaboration and Interaction Systems
July 23, 2026 ยท View on GitHub
๐ Our survey has been accepted to ACL 2026!

Welcome to Awesome-Human-Agent-Collaboration-Interaction-Systems! ๐ This is the repo for our Survey on LLM-Based Human-Agent Collaboration and Interaction Systems, accepted to ACL 2026.
๐ Introduction
Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-based agents still face significant challenges, including (1) limited reliability due to hallucinations, (2) difficulty in handling complex tasks, and (3) substantial safety and ethical risks, all of which limit their feasibility and trustworthiness in real-world applications.
LLM-based human-agent collaboration systems are interactive frameworks where humans actively provide (1) additional information, (2) feedback, or (3) control during interaction with LLM-powered agents to enhance system performance, reliability, and safety. These human-agent collaboration systems enable humans and LLM-based agents to collaborate effectively by leveraging their complementary strengths. For a detailed introduction, please refer to our survey paper: LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey.
Our goal with this project is to build an exhaustive collection of awesome resources relevant to LLM-Based Human-Agent/AI Collaboration and Interaction Systems, encompassing papers, repositories, and more to foster further research and innovation in this rapidly evolving interdisciplinary field of human-ai collaboration. ๐ค Contributions are welcome! ๐ค If you have recommended papers, resources or suggestions, please submit pull requests, open issues or contact us. We will keep updating our repo & survey paper.
๐ Contents
- ๐ Latest Research Papers
- ๐ Applications, Datasets & Benchmarks
- ๐ป Web Navigation & Computer Use
- ๐จ๐ปโ๐ป Software Engineering, Coding
- ๐ค Embodied AI, Robotics
- ๐ฌ Conversation System
- ๐ Data Science, Scientific Discovery
- ๐ฎ Gaming
- ๐ฐ Finance
- ๐ฅ Healthcare, Medicine
- ๐งฉ General-Purpose Assistants, Cross-Domain
- ๐๏ธ Retail, Telecom
- ๐ฉ๏ธ Travel
- โ๏ธ Writing
- ๐ Taxonomy
- ๐ Contributing
- ๐ Citation
๐ Latest Research Papers
(ยฉ๏ธclick here back to table of contents๐๐ป)
๐ค Contributions are welcome! If you have recommended papers and resources, please submit pull requests or open issues.
-
[2026-07-18] [arXiv 2026] Just A Rather Very Intelligent Spoken Agent (JarvisBench) [Project]
-
[2026-07-07] [arXiv 2026] LLM Agents for Deliberative Collaboration: A Study on Joint Decision Making Under Partial Observability
-
[2026-07-05] [arXiv 2026] HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation
-
[2026-06-17] [arXiv 2026] Uncertainty Decomposition for Clarification Seeking in LLM Agents
-
[2026-06-17] [arXiv 2026] Learning User Simulators with Turing Rewards
-
[2026-06-11] [arXiv 2026] Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents (TRACE)
-
[2026-06-07] [arXiv 2026] PerspectiveGap: A Benchmark for Multi-Agent Orchestration Prompting
-
[2026-06-04] [arXiv 2026] Re-Centering Humans in LLM Personalization
-
[2026-06-04] [ICML 2026] CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement
-
[2026-06-03] [arXiv 2026] Human Oversight of Agentic Systems in Practice: Examining the Oversight Work, Challenges, and Heuristics of Developers Using Software Agents
-
[2026-06-02] [arXiv 2026] Uncertainty-Aware Clarification in LLM Agents with Information Gain
-
[2026-05-27] [FAccT 2026] Not All Uncertainty Is Equal: How Uncertainty Granularity Shapes Human Verification in LLM-Assisted Decision Making
-
[2026-05-26] [arXiv 2026] VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
-
[2026-05-23] [arXiv 2026] Reframing LLM Agent Security as an Agent-Human Interaction Problem
-
[2026-05-19] [arXiv 2026] Reinforcing Human Behavior Simulation via Verbal Feedback (DITTO & SOUL)
-
[2026-05-11] [arXiv 2026] ECHO: Explainable Co-editing with Human-in-the-loop Operations for Presentation Refinement
-
[2026-05-09] [arXiv 2026] AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
-
[2026-05-08] [arXiv 2026] SalesSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators
-
[2026-04-24] [arXiv 2026] A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows
-
[2026-04-20] [arXiv 2026] CollabSkill: Evaluating Human-Agent Collaboration On Real-World Tasks
-
[2026-04-07] [arXiv 2026] Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge
-
[2026-04-01] [arXiv 2026] When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
-
[2026-03-30] [arXiv 2026] ViviDoc: Generating Interactive Documents through Human-Agent Collaboration
-
[2026-03-27] [arXiv 2026] Ask or Assume? Uncertainty-Aware Clarification-Seeking in Coding Agents
-
[2026-03-21] [arXiv 2026] User Preference Modeling for Conversational LLM Agents: Weak Rewards from Retrieval-Augmented Interaction (VARS)
-
[2026-03-20] [arXiv 2026] LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
-
[2026-03-19] [arXiv 2026] AgentDS: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science [Project]
-
[2026-02-28] [arXiv 2026] InfoPO: Information-Driven Policy Optimization for User-Centric Agents
-
[2026-02-19] [arXiv 2026] Modeling Distinct Human Interaction in Web Agents (CowCorpus)
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[2026-02-18] [arXiv 2026] Learning Personalized Agents from Human Feedback
-
[2026-02-18] [arXiv 2026] Overseeing Agents Without Constant Oversight: Challenges and Opportunities
-
[2026-01-10] [arXiv 2026] Value of Information: A Framework for Human-Agent Communication
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[2026-01-01] [arXiv 2026] Progressive Ideation using an Agentic AI Framework for Human-AI Co-Creation (MIDAS)
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[2025-11-30] [arXiv 2025] CentaurEval: Benchmarking Human-in-the-Loop Value in Agentic Coding
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[2025-11-04] [arXiv 2025] Training Proactive and Personalized LLM Agents
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[2025-10-15] [arXiv 2025] Training LLM Agents to Empower Humans
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[2025-10-10] [arXiv 2025] How can we assess human-agent interactions? Case studies in software agent design
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[2025-10-07] [arXiv 2025] RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback
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[2025-09-24] [arXiv 2025] UserRL: Training Proactive User-Centric Agent via Reinforcement Learning
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[2025-08-26] [arXiv 2025] MUA-RL: Multi-turn User-interacting Agent Reinforcement Learning for agentic tool use
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[2025-08-20] [arXiv 2025] aiXiv: A Next-Generation Open Access Ecosystem for Scientific Discovery Generated by AI Scientists
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[2025-07-31] [arXiv 2025] MemoCue: Empowering LLM-Based Agents for Human Memory Recall via Strategy-Guided Querying
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[2025-07-30] [arXiv 2025] Magentic-UI: Towards Human-in-the-loop Agentic Systems
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[2025-07-29] [arXiv 2025] UserBench: An Interactive Gym Environment for User-Centric Agents
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[2025-07-28] [arXiv 2025] GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis
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[2025-07-23] [arXiv 2025] Enabling Self-Improving Agents to Learn at Test Time With Human-In-The-Loop Guidance
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[2025-07-21] [arXiv 2025] Interaction as Intelligence: Deep Research With Human-AI Partnership
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[2025-06-13] [arXiv 2025] Interaction, Process, Infrastructure: A Unified Architecture for Human-Agent Collaboration
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[2025-06-11] [arXiv 2025] A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy
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[2025-06-09] [arXiv 2025] ฯ2-Bench: Evaluating Conversational Agents in a Dual-Control Environment
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[2025-06-06] [arXiv 2025] Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce
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[2025-05-24] [ICLR 2025] Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training [Code]
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[2025-05-23] [arXiv 2025] Collaborative Memory: Multi-User Memory Sharing in LLM Agents with Dynamic Access Control
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[2025-05-21] [arXiv 2025] Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wild
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[2025-05-16] [arXiv 2025] XtraGPT: LLMs for Human-AI Collaboration on Controllable Academic Paper Revision
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[2025-05-05] [arXiv 2025] SymbioticRAG: Enhancing Document Intelligence Through Human-LLM Symbiotic Collaboration
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[2025-05-01] [arXiv 2025] LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey
-
[2025-04-13] [arXiv 2025] EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety
-
[2025-04-11] [arXiv 2025] MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft
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[2025-04-04] [arXiv 2025] APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay
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[2025-03-24] [ACL 2025 Findings] SPHERE: An Evaluation Card for Human-AI Systems
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[2025-03-19] [arXiv 2025] SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
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[2025-03-10] [arXiv 2025] Experimental Exploration: Investigating Cooperative Interaction Behavior Between Humans and Large Language Model Agents
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[2025-03-04] [arXiv 2025] FinArena: A Human-Agent Collaboration Framework for Financial Market Analysis and Forecasting
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[2025-03-03] [ICML 2025] M3HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
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[2025-02-27] [ICLR 2025] ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
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[2025-02-17] [ACL 2025] Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration
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[2025-02-02] [ICML 2025] CollabLLM: From Passive Responders to Active Collaborators
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[2025-01-28] [NAACL 2025 Demo] CowPilot: A Framework for Autonomous and Human-Agent Collaborative Web Navigation
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[2024-12-25] [IROS 2024] To Help or Not to Help: LLM-based Attentive Support for Human-Robot Group Interactions
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[2024-12-20] [arXiv 2024] Collaborative Gym: A Framework for Enabling and Evaluating Human-Agent Collaboration
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[2024-12-08] [arXiv 2024] Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension
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[2024-11-26] [arXiv 2024] Effect of Adaptive Communication Support on LLM-powered Human-Robot Collaboration
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[2024-10-31] [ICLR 2025] PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks
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[2024-10-30] [ICLR 2025] ACC-Collab: An Actor-Critic Approach to Multi-Agent LLM Collaboration
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[2024-10-16] [ICLR 2025] Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance
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[2024-09-26] [arXiv 2024] AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment
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[2024-09-25] [arXiv 2024] AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agents
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[2024-09-13] [arXiv 2024] Mutual Theory of Mind in Human-AI Collaboration: An Empirical Study with LLM-driven AI Agents in a Real-time Shared Workspace Task
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[2024-08-27] [EMNLP 2024] Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
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[2024-07-12] [SME 2024] Human-LLM collaboration in generative design for customization
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[2024-06-20] [RAL 2024] Enhancing the LLM-Based Robot Manipulation Through Human-Robot Collaboration
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[2024-06-18] [ICLR 2025] ฯ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
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[2024-06-17] [EMNLP 2024] Ask-before-Plan: Proactive Language Agents for Real-World Planning
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[2024-06-14] [NeurIPS 2024] DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
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[2024-06-04] [CASE 2024] Enhancing Human-Robot Collaborative Assembly in Manufacturing Systems Using Large Language Models
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[2024-05-30] [arXiv 2024] Safe Multi-agent Reinforcement Learning with Natural Language Constraints
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[2024-05-27] [AAAI 2025] REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents using Information Relevance and Relative Proximity
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[2024-04-23] [NeurIPS 2024] Aligning LLM Agents by Learning Latent Preference from User Edits
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[2024-04-18] [arXiv 2024] AgentCoord: Visually Exploring Coordination Strategy for LLM-based Multi-Agent Collaboration
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[2024-04-05] [IUI 2024] PDFChatAnnotator: A Human-LLM Collaborative Multi-Modal Data Annotation Tool for PDF-Format Catalogs
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[2024-03-19] [arXiv 2024] Embodied LLM Agents Learn to Cooperate in Organized Teams
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[2024-02-08] [arXiv 2024] WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
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[2024-02-07] [NeurIPS 2024] Can Large Language Model Agents Simulate Human Trust Behavior?
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[2024-01-25] [arXiv 2024] A2C: A Modular Multi-stage Collaborative Decision Framework for Human-AI Teams
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[2023-12-23] [AAMAS 2024] LLM-Powered Hierarchical Language Agent for Real-time Human-AI Coordination
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[2023-10-18] [ICLR 2024] SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents
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[2023-09-19] [WACV 2024] Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles
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[2023-09-19] [ICLR 2024] MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
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[2023-09-18] [NAACL 2024] MindAgent: Emergent Gaming Interaction
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[2023-08-01] [ICML 2023] MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
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[2023-07-05] [ICLR 2024] Building Cooperative Embodied Agents Modularly with Large Language Models
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[2023-07-04] [ICML 2023] Embodied Task Planning with Large Language Models
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[2023-06-01] [IEEE 2023] Improved Trust in Human-Robot Collaboration With ChatGPT
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[2023-05-22] [EACL 2024] Investigating Agency of LLMs in Human-AI Collaboration Tasks
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[2023-04-21] [EACL 2024] Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback
๐ Applications, Datasets & Benchmarks
(ยฉ๏ธclick here back to table of contents๐๐ป)
๐ป Web Navigation & Computer Use
-
[2026-04-01] [arXiv 2026] When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
-
[2026-03-20] [arXiv 2026] LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks
-
[2026-02-19] [arXiv 2026] Modeling Distinct Human Interaction in Web Agents (CowCorpus)
-
[2026-02-18] [arXiv 2026] Overseeing Agents Without Constant Oversight: Challenges and Opportunities
๐จ๐ปโ๐ป Software Engineering, Coding
-
[2026-06-11] [arXiv 2026] Getting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents (TRACE)
-
[2026-06-03] [arXiv 2026] Human Oversight of Agentic Systems in Practice: Examining the Oversight Work, Challenges, and Heuristics of Developers Using Software Agents
-
[2026-05-09] [arXiv 2026] AgentCollabBench: Diagnosing When Good Agents Make Bad Collaborators
-
[2026-04-20] [arXiv 2026] CollabSkill: Evaluating Human-Agent Collaboration On Real-World Tasks
-
[2026-03-27] [arXiv 2026] Ask or Assume? Uncertainty-Aware Clarification-Seeking in Coding Agents
-
[2025-10-07] [arXiv 2025] RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback
-
[2025-07-30] [arXiv 2025] Magentic-UI: Towards Human-in-the-loop Agentic Systems
-
[2025-03-19] [arXiv 2025] SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks
-
[2025-02-27] [ICLR 2025] ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
-
[2023-09-19] [ICLR 2024] MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
-
[2023-06-26] [NeurIPS 2023] InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
๐ค Embodied AI, Robotics
-
[2026-07-07] [arXiv 2026] LLM Agents for Deliberative Collaboration: A Study on Joint Decision Making Under Partial Observability
-
[2024-10-31] [ICLR 2025] PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks
-
[2023-09-19] [ICLR 2024] MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
-
[2023-07-05] [ICLR 2024] Building Cooperative Embodied Agents Modularly with Large Language Models
-
[2023-07-04] [arXiv 2023] Embodied Task Planning with Large Language Models
-
[2023-04-21] [EACL 2024 Findings] Improving Grounded Language Understanding in a Collaborative Environment by Interacting with Agents Through Help Feedback
๐ฌ Conversation System
-
[2026-06-17] [arXiv 2026] Learning User Simulators with Turing Rewards
-
[2026-06-04] [arXiv 2026] Re-Centering Humans in LLM Personalization
-
[2026-05-26] [arXiv 2026] VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
-
[2026-05-19] [arXiv 2026] Reinforcing Human Behavior Simulation via Verbal Feedback (DITTO & SOUL)
-
[2026-03-21] [arXiv 2026] User Preference Modeling for Conversational LLM Agents: Weak Rewards from Retrieval-Augmented Interaction (VARS)
-
[2026-02-28] [arXiv 2026] InfoPO: Information-Driven Policy Optimization for User-Centric Agents
-
[2026-02-18] [arXiv 2026] Learning Personalized Agents from Human Feedback
-
[2026-01-10] [arXiv 2026] Value of Information: A Framework for Human-Agent Communication
-
[2025-09-24] [arXiv 2025] UserRL: Training Proactive User-Centric Agent via Reinforcement Learning
-
[2025-05-24] [ICLR 2025] Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training [Code]
-
[2024-08-27] [EMNLP 2024] Into the Unknown Unknowns: Engaged Human Learning through Participation in Language Model Agent Conversations
-
[2024-02-08] [arXiv 2024] WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
-
[2023-09-19] [ICLR 2024] MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback
๐ Data Science, Scientific Discovery
-
[2026-06-07] [arXiv 2026] PerspectiveGap: A Benchmark for Multi-Agent Orchestration Prompting
-
[2026-03-19] [arXiv 2026] AgentDS: Benchmarking the Future of Human-AI Collaboration in Domain-Specific Data Science [Project]
๐ฎ Gaming
-
[2026-06-04] [ICML 2026] CollabBench: Benchmarking and Unleashing Collaborative Ability of LLMs with Diverse Players via Proactive Engagement
-
[2025-04-11] [arXiv 2025] MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft
-
[2023-09-18] [ICLR 2024] MindAgent: Emergent Gaming Interaction
๐ฐ Finance
- [2025-03-04] [arXiv 2025] FinArena: A Human-Agent Collaboration Framework for Financial Market Analysis and Forecasting Data Link
๐ฅ Healthcare, Medicine
-
[2026-05-27] [FAccT 2026] Not All Uncertainty Is Equal: How Uncertainty Granularity Shapes Human Verification in LLM-Assisted Decision Making
-
[2025-07-28] [arXiv 2025] GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis
-
[2025-04-13] [arXiv 2025] EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety
๐งฉ General-Purpose Assistants, Cross-Domain
-
[2026-07-18] [arXiv 2026] Just A Rather Very Intelligent Spoken Agent (JarvisBench) [Project]
-
[2026-07-05] [arXiv 2026] HAS-Bench: Evaluating LLM-Based Human-Agent Systems under Configurable Human Participation
-
[2026-06-17] [arXiv 2026] Uncertainty Decomposition for Clarification Seeking in LLM Agents
-
[2026-06-02] [arXiv 2026] Uncertainty-Aware Clarification in LLM Agents with Information Gain
-
[2026-05-23] [arXiv 2026] Reframing LLM Agent Security as an Agent-Human Interaction Problem
-
[2026-04-24] [arXiv 2026] A Decoupled Human-in-the-Loop System for Controlled Autonomy in Agentic Workflows
-
[2026-04-07] [arXiv 2026] Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge
๐๏ธ Retail, Telecom
-
[2026-05-26] [arXiv 2026] VitaBench 2.0: Evaluating Personalized and Proactive Agents in Long-Term User Interactions
-
[2026-05-08] [arXiv 2026] SalesSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators
-
[2025-06-09] [arXiv 2025] ฯ2-Bench: Evaluating Conversational Agents in a Dual-Control Environment
-
[2024-06-18] [ICLR 2025] ฯ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
๐ฉ๏ธ Travel
-
[2025-07-29] [arXiv 2025] UserBench: An Interactive Gym Environment for User-Centric Agents
-
[2025-06-09] [arXiv 2025] ฯ2-Bench: Evaluating Conversational Agents in a Dual-Control Environment
-
[2024-06-18] [ICLR 2025] ฯ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains
โ๏ธ Writing
-
[2026-05-11] [arXiv 2026] ECHO: Explainable Co-editing with Human-in-the-loop Operations for Presentation Refinement
-
[2026-03-02] [arXiv 2026] ViviDoc: Generating Interactive Documents through Human-Agent Collaboration
-
[2026-01-01] [arXiv 2026] Progressive Ideation using an Agentic AI Framework for Human-AI Co-Creation (MIDAS)
-
[2025-05-21] [arXiv 2025] Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wild
-
[2025-05-16] [arXiv 2025] XtraGPT: LLMs for Human-AI Collaboration on Controllable Academic Paper Revision
๐ Taxonomy
(ยฉ๏ธclick here back to table of contents๐๐ป)
For a detailed introduction of the taxonomy, please refer to Section 3 in our survey paper: LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey.

๐ค Human Feedback
(ยฉ๏ธclick here back to table of contents๐๐ป)
Human Feedback can occur during different phases in various types and granularities. In the following table, we summarize different dimensions of Human Feedback in LLM-based human-agent systems, including feedback type, granularity, and phase. For each dimension, a summary, key characteristics, and example works are provided for comparison. More details are in Section 3.2 of our survey paper.

๐ Interaction
(ยฉ๏ธclick here back to table of contents๐๐ป)
๐๏ธ Orchestration
(ยฉ๏ธclick here back to table of contents๐๐ป)
๐ฌ Communication
(ยฉ๏ธclick here back to table of contents๐๐ป)
๐ Contributing
(ยฉ๏ธclick here back to table of contents๐๐ป)
Contributions are welcome! If you have relevant papers, code, or insights, feel free to submit a request ๐ค.
๐ Citation
(ยฉ๏ธclick here back to table of contents๐๐ป)
If you find this repository useful, please consider citing our papers ๐:
The survey has been accepted to ACL 2026; the BibTeX below will be updated to the proceedings entry once it is available.
@misc{zou2025llmbasedhumanagentcollaborationinteraction,
title={LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey},
author={Henry Peng Zou and Wei-Chieh Huang and Yaozu Wu and Yankai Chen and Chunyu Miao and Hoang Nguyen and Yue Zhou and Weizhi Zhang and Liancheng Fang and Langzhou He and Yangning Li and Dongyuan Li and Renhe Jiang and Xue Liu and Philip S. Yu},
year={2025},
eprint={2505.00753},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.00753},
}
@misc{zou2025collaborativeintelligencehumanagentsystems,
title={A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy},
author={Henry Peng Zou and Wei-Chieh Huang and Yaozu Wu and Chunyu Miao and Dongyuan Li and Aiwei Liu and Yue Zhou and Yankai Chen and Weizhi Zhang and Yangning Li and Liancheng Fang and Renhe Jiang and Philip S. Yu},
year={2025},
eprint={2506.09420},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2506.09420},
}