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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A comprehensive list of PAPERS, CODEBASES, and, DATASETS on Decision Making using Foundation Models including LLMs and VLMs.
| Date | Stars |
|---|---|
| 2026-07-31 | 383 |
| 2026-08-04 | 383 |
| 2026-08-06 | 383 |
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# **Awesome-LLM-Decision-Making** # 2023 up-to-date list of PAPERS, CODEBASES, and BENCHMARKS on Decision Making using Foundation Models including LLMs and VLMs. Please feel free to send me pull requests or contact me to correct any mistakes. --- ## **Table of Contents** ## - [Survey of Foundation Models in Decision Making](#Survey) - [Foundation Models as World Models](#World-Models) - [Foundation Models as Reward Models](#Reward-Models) - [Foundation Models as Agent Models](#Agent-Models) - [Foundation Models as Representation Encoders](#Encoders) - [Multi-modal Decision Making Benchmarks](#Benchmark) --- ## **Paper** ## ### **Survey** ### - "A survey of reinforcement learning informed by natural language." arXiv, 2019. [[paper]](https://arxiv.org/pdf/1906.03926) - "A Survey on Transformers in Reinforcement Learning." arXiv, 2023. [[paper]](https://arxiv.org/pdf/2301.03044) - "Foundation models for decision making: Problems, methods, and opportunities." arXiv, 2023. [[paper]](https://arxiv.org/pdf/2303.04129) - "A Survey of Large Language Models." arXiv, June 2023. [[paper]](https://arxiv.org/pdf/2303.18223)[[code]](https://github.com/RUCAIBox/LLMSurvey) - "A Survey on Large Language Model based Autonomous Agents." arXiv, Aug 2023. [[paper]](https://arxiv.org/pdf/2308.11432)[[code]](https://github.com/Paitesanshi/LLM-Agent-Survey) - "Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security." arXiv, Jan 2024. [[paper]](https://arxiv.org/pdf/2401.05459.pdf)[[code]](https://github.com/MobileLLM/Personal_LLM_Agents_Survey) ### **World Models** ### - **IRIS**: "Transformers are sample efficient world models." ICLR, 2023. [[paper]](https://arxiv.org/pdf/2209.00588)[[code]](https://github.com/eloialonso/iris) - **UniPi**: "Learning Universal Policies via Text-Guided Video Generation." arXiv, 2023.[[paper]](https://arxiv.org/pdf/2302.00111)[[website]](https://universal-policy.github.io/unipi/) - **Dynalang**： "Learning to Model the World with Language." arXiv, July 2023. [[paper]](https://arxiv.org/pdf/2308.01399)[[website]](https://dynalang.github.io/)[[code]](https://github.com/jlin816/dynalang) ### **Reward Models** ### - **EAGER**: "EAGER: Asking and Answering Questions for Automatic Reward Shaping in Language-guided RL." NIPS, 2022. [[paper]](https://proceedings.neurips.cc/paper_files/paper/2022/file/50eb39ab717507cccbe2b8590de32030-Paper-Conference.pdf)[[code]](https://github.com/flowersteam/eager) - "Reward design with language models." ICLR, 2023. [[paper]](https://arxiv.org/pdf/2303.00001)[[code]](https://github.com/minaek/reward_design_with_llms) - **ELLM**: "Guiding Pretraining in Reinforcement Learning with Large Language Models." arXiv, 2023. [[paper]](https://arxiv.org/pdf/2302.06692) - "Language to Rewards for Robotic Skill Synthesis." arXiv, June 2023. [[paper]](https://arxiv.org/pdf/2306.08647)[[website]](https://language-to-reward.github.io/) - "Vision-Language Models are Zero-Shot Reward Models for Reinforcement Learning." arXiv, Oct 2023. [[paper]](https://arxiv.org/pdf/2310.12921.pdf) - **Eureka**: "Eureka: Human-Level Reward Design via Coding Large Language Models." arXiv, Oct 2023. [[paper]](https://arxiv.org/pdf/2310.12931.pdf)[[wensite]](https://eureka-research.github.io/)[[code]](https://github.com/eureka-research/Eureka) ### **Agent Models** ### - **Generative Agent** - **FILM**: "Film: Following instructions in language with modular methods." ICLR, 2022. [[paper]](https://arxiv.org/pdf/2110.07342)[[code]](https://soyeonm.github.io/FILM_webpage/)[[website]](https://soyeonm.github.io/FILM_webpage/) - "Grounding large language models in interactive environments with online reinforcement learning." arXiv, 2023. [[paper]](https://arxiv.org/pdf/2302.02662)[[code]](https://github.com/flowersteam/Grounding_LLMs_with_online_RL) - **Inner Monologue**: "Inner monologue: Embodied reasoning through planning with language models." arXiv, 2022. [[paper]](https://arxiv.org/pd
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