LLM-Agents-Papers repo

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• LLM-Agents-Papers/README.md at main · AGI-Edgerunners/LLM-Agents-Papers

LLM-Agents-Papers

✍️ Description

Last Updated Time: 2024/7/1

A repo lists papers related to LLM based agent. Includes

• Survey
• Planning, Feedback&Reflection, Memory Mechanism
• Role Playing, Game Playing, Tool Usage&Human-Agent Interaction
• Benchmark&Evaluation, Environment&Platform
• Agent Framework, Multi-Agent System
• Agent Fine-tuning

💛 Recommendation

For more comprehensive reading, we also recommend other paper lists:

• zjunlp/LLMAgentPapers: Must-read Papers on Large Language Model Agents.
• teacherpeterpan/self-correction-llm-papers: This is a collection of research papers for Self-Correcting Large Language Models with Automated Feedback.
• Paitesanshi/LLM-Agent-Survey: A Survey on LLM-based Autonomous Agents.
• woooodyy/llm-agent-paper-list: Must-read papers for LLM-based agents.
• git-disl/awesome-LLM-game-agent-papers: Must-read papers for LLM-based Game agents.

📰 Papers

Survey

• [2024/06/09] A Survey on LLM-Based Agents: Common Workflows and Reusable LLM-Profiled Components | [paper] | [code]

• [2024/06/03] Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization | [paper] | [code]

• [2024/06/01] Multi-Modal and Multi-Agent Systems Meet Rationality: A Survey | [paper] | [code]

• [2024/05/16] Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents | [paper] | [code]

• [2024/04/17] The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey | [paper] | [code]

• [2024/04/17] Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions | [paper] | [code]

• [2024/04/03] Empowering Biomedical Discovery with AI Agents | [paper] | [code]

• [2024/04/02] A Survey on Large Language Model-Based Game Agents | [paper] | [code]

• [2024/03/26] Large Language Models for Human-Robot Interaction: Opportunities and Risks | [paper] | [code]

• [2024/03/07] Promising and worth-to-try future directions for advancing state-of-the-art surrogates methods of agent-based models in social and health computational sciences | [paper] | [code]

• [2024/02/28] Large Language Models and Games: A Survey and Roadmap | [paper] | [code]

• [2024/02/28] A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems | [paper] | [code]

• [2024/02/07] Can Large Language Model Agents Simulate Human Trust Behaviors? | [paper] | [code]

• [2024/02/06] Prioritizing Safeguarding Over Autonomy: Risks of LLM Agents for Science | [paper] | [code]

• [2024/02/05] Understanding the planning of LLM agents: A survey | [paper] | [code]

• [2024/02/02] Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions | [paper] | [code]

• [2024/01/01] If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents | [paper] | [code]

• [2023/12/31] A Survey of Personality, Persona, and Profile in Conversational Agents and Chatbots | [paper] | [code]

• [2023/12/19] Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives | [paper] | [code]

• [2023/09/14] The Rise and Potential of Large Language Model Based Agents: A Survey | [paper] | [code]

• [2023/08/22] A Survey on Large Language Model based Autonomous Agents | [paper] | [code]

• [2023/06/27] Next Steps for Human-Centered Generative AI: A Technical Perspective | [paper] | [code]

• [2023/04/06] Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions | [paper] | [code]

Planning

• [2024/06/17] RePrompt: Planning by Automatic Prompt Engineering for Large Language Models Agents | [paper] | [code]

• [2024/06/06] Tool-Planner: Dynamic Solution Tree Planning for Large Language Model with Tool Clustering | [paper] | [code]

• [2024/05/28] A Human-Like Reasoning Framework for Multi-Phases Planning Task with Large Language Models | [paper] | [code]

• [2024/05/27] LLM-Based Cooperative Agents using Information Relevance and Plan Validation | [paper] | [code]

• [2024/05/24] Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models | [paper] | [code]

• [2024/04/28] Logic Agent: Enhancing Validity with Logic Rule Invocation | [paper] | [code]

• [2024/04/21] Socratic Planner: Inquiry-Based Zero-Shot Planning for Embodied Instruction Following | [paper] | [code]

• [2024/03/13] AutoGuide: Automated Generation and Selection of State-Aware Guidelines for Large Language Model Agents | [paper] | [code]

• [2024/03/12] AesopAgent: Agent-driven Evolutionary System on Story-to-Video Production | [paper] | [code]

• [2024/03/11] Strength Lies in Differences! Towards Effective Non-collaborative Dialogues via Tailored Strategy Planning | [paper] | [code]

• [2024/03/10] TRAD: Enhancing LLM Agents with Step-Wise Thought Retrieval and Aligned Decision | [paper] | [code]

• [2024/03/05] KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents | [paper] | [code]

• [2024/03/05] Language Guided Exploration for RL Agents in Text Environments | [paper] | [code]

• [2024/02/29] PlanGPT: Enhancing Urban Planning with Tailored Language Model and Efficient Retrieval | [paper] | [code]

• [2024/02/28] Data Interpreter: An LLM Agent For Data Science | [paper] | [code]

• [2024/02/18] What's the Plan? Evaluating and Developing Planning-Aware Techniques for LLMs | [paper] | [code]

• [2024/02/18] PreAct: Predicting Future in ReAct Enhances Agent's Planning Ability | [paper] | [code]

• [2024/02/16] When is Tree Search Useful for LLM Planning? It Depends on the Discriminator | [paper] | [code]

• [2024/02/09] Introspective Planning: Guiding Language-Enabled Agents to Refine Their Own Uncertainty | [paper] | [code]

• [2024/02/06] RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents | [paper] | [code]

• [2024/02/02] TravelPlanner: A Benchmark for Real-World Planning with Language Agents | [paper] | [code]

• [2024/01/10] AUTOACT: Automatic Agent Learning from Scratch via Self-Planning | [paper] | [code]

• [2023/11/19] TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systems | [paper] | [code]

• [2023/10/09] Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena | [paper] | [code]

• [2023/08/07] TPTU: Task Planning and Tool Usage of Large Language Model-based AI Agents | [paper] | [code]

• [2023/05/26] AdaPlanner: Adaptive Planning from Feedback with Language Models | [paper] | [code]

• [2023/05/24] Reasoning with Language Model is Planning with World Model | [paper] | [code]

• [2023/05/24] Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning | [paper] | [code]

• [2023/03/29] Plan4MC: Skill Reinforcement Learning and Planning for Open-World Minecraft Tasks | [paper] | [code]

• [2023/02/03] Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents | [paper] | [code]

• [2022/12/08] LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models | [paper] | [code]

Feedback&Reflection

• [2024/06/05] LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback | [paper] | [code]

• [2024/03/18] QueryAgent: A Reliable and Efficient Reasoning Framework with Environmental Feedback based Self-Correction | [paper] | [code]

• [2024/03/17] Improving Dialogue Agents by Decomposing One Global Explicit Annotation with Local Implicit Multimodal Feedback | [paper] | [code]

• [2024/03/08] ChatASU: Evoking LLM's Reflexion to Truly Understand Aspect Sentiment in Dialogues | [paper] | [code]

• [2024/03/04] Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents | [paper] | [code]

• [2024/02/27] Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization | [[

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