| Self-Instruct: Aligning language models with self-generated instructions | arxiv 2023 | https://github.com/yizhongw/self-instruct |
| WizardLM: Empowering large language models to follow complex instructions | arxiv 2023 | https://github.com/nlpxucan/WizardLM |
| Code Llama: Open foundation models for code | arxiv 2023 | https://github.com/meta-llama/codellama |
| Scaling Relationship on Learning Mathematical Reasoning with Large Language Models | arxiv 2023 | https://github.com/OFA-Sys/gsm8k-ScRel |
| Self-Translate-Train: A Simple but Strong Baseline for Cross-lingual Transfer of Large Language Models | arxiv 2024 | - |
| CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement Learning | NeurIPS 2022 | https://github.com/salesforce/CodeRL |
| Self-play fine-tuning converts weak language models to strong language models | arxiv 2024 | https://github.com/uclaml/SPIN |
| Language models can teach themselves to program better | arxiv 2022 | https://github.com/microsoft/PythonProgrammingPuzzles |
| DeepSeek-Prover: Advancing theorem proving in LLMs through large-scale synthetic data | arxiv 2024 | - |
| STaR: Bootstrapping reasoning with reasoning | arxiv 2022 | - |
| Reinforced Self-Training (ReST) for Language Modeling | arxiv 2023 | - |
| Beyond human data: Scaling self-training for problem-solving with language models | arxiv 2023 | - |
| Code alpaca: An instruction-following llama model for code generation | github 2023 | https://github.com/sahil280114/codealpaca |
| Stanford Alpaca: An Instruction-following LLaMA Model | github 2023 | https://github.com/tatsu-lab/stanford_alpaca |
| Huatuo: Tuning llama model with chinese medical knowledge | arxiv 2023 | https://github.com/SCIR-HI/Huatuo-Llama-Med-Chinese |
| Magicoder: Source code is all you need | arxiv 2023 | https://github.com/ise-uiuc/magicoder |
| Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models | STEP | https://github.com/ritaranx/ClinGen |
| Unnatural instructions: Tuning language models with (almost) no human labor | arxiv 2022 | https://github.com/orhonovich/unnatural-instructions |
| Baize: An open-source chat model with parameter-efficient tuning on self-chat data | arxiv 2023 | https://github.com/project-baize/baize-chatbot |
| Impossible Distillation for Paraphrasing and Summarization: How to Make High-quality Lemonade out of Small, Low-quality Model | arxiv 2023 | - |
| Llm2llm: Boosting llms with novel iterative data enhancement | arxiv 2024 | https://github.com/SqueezeAILab/LLM2LLM |
| WizardCode: Empowering code large language models with Evol-Instruct | arxiv 2023 | https://github.com/nlpxucan/WizardLM |
| Generative AI for Math: Abel | arxiv 2024 | - |
| Orca: Progressive learning from complex explanation traces of gpt-4 | arxiv 2023 | https://www.microsoft.com/en-us/research/project/orca/ |
| Orca 2: Teaching small language models how to reason | arxiv 2023 | - |
| Mammoth: Building math generalist models through hybrid instruction tuning | arxiv 2023 | https://tiger-ai-lab.github.io/MAmmoTH/ |
| Lab: Large-scale alignment for chatbots | arxiv 2024 | - |
| Synthetic data (almost) from scratch: Generalized instruction tuning for language models | arxiv 2024 | https://thegenerality.com/agi/ |
| SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding | arxiv 2024 | https://github.com/dptech-corp/Uni-SMART/tree/main/SciLitLLM |
| Llava-med: Training a large language-and-vision assistant for biomedicine in one day | arxiv 2024 | https://github.com/microsoft/LLaVA-Med |
| Visual instruction tuning | NIPS 2024 | - |
| Chartllama: A multimodal llm for chart understanding and generation | arxiv 2023 | https://tingxueronghua.github.io/ChartLlama/ |
| Sharegpt4v: Improving large multi-modal models with better captions | arxiv 2023 | https://sharegpt4v.github.io/ |
| Next-gpt: Any-to-any multimodal llm | arxiv 2023 | https://next-gpt.github.io/ |
| Does synthetic data generation of llms help clinical text mining? | arxiv 2023 | - |
| Ultramedical: Building specialized generalists in biomedicine | arxiv 2024 | https://github.com/TsinghuaC3I/UltraMedical |
| Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images! | arxiv 2023 | https://github.com/codezakh/SelTDA |
| MetaMeth: Bootstap your own mathematical questions for large language models | arxiv 2024 | https://meta-math.github.io/ |
| Symbol tuning improves in-context learning in language models | arxiv 2023 | - |
| DISC-MedLLM: Bridging General Large Language Models and Real-World Medical Consultation | arxiv 2023 | https://github.com/FudanDISC/DISC-MedLLM |
| Mathgenie: Generating synthetic data with question back-translation for enhancing mathematical reasoning of llms | arxiv 2024 | - |
| BianQue: Balancing the Questioning and Suggestion Ability of Health LLMs with Multi-turn Health Conversations Polished by ChatGPT | arxiv 2023 | https://github.com/scutcyr/BianQue |