LLM agents, etc.

• See the related work of Chen 2023 for a nice overview.
• Wang et al 2023 - A Survey on Large Language Model based Autonomous Agents
  • LLM Agent Survey (github) - from the above survey, continuously updated
• Li et al 2025 - A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning
  • LLM Agent Survey (github) - from the above survey, continuously updated
• Xi et al 2023 - The Rise and Potential of Large Language Model Based Agents: A Survey
• Wang et al 2024 - Large Language Model based Multi-Agents: A Survey of Progress and Challenges
• Masterman et al 2024 - The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey
• Sapkota et al 2025 - AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges v4 (better formatting)
• Architectures
  • Sumers et al 2024 - Cognitive Architectures for Language Agents
• Memory Architectures
  • Rasmussen et al 2025 - Zep: A Temporal Knowledge Graph Architecture for Agent Memory
• Alignment
  • Zheng et al 2025 - Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives
• Multi-Agents
  • Tran et al 2025 - Multi-Agent Collaboration Mechanisms: A Survey of LLMs
• Applications
  • GUI Agents
    • Wang et al 2024 - GUI Agents with Foundation Models: A Comprehensive Survey
    • Zhang et al 2024 - Large Language Model-Brained GUI Agents: A Survey
  • Personal Agents
    • Li et al 2024 - Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

• Key Method Papers
  • Yao et al 2022 - ReAct: Synergizing Reasoning and Acting in Language Models - The basis of LangChain. See the Webshop experiments section 4 and appendix D.3.
    • Follow-up work: Jiao et al 2024 - Learning Planning-based Reasoning via Trajectories Collection and Process Reward Synthesizing
  • Shinn et al 2023 - Reflexion: Language Agents with Verbal Reinforcement Learning
  • Zhao et al 2023 - ExpeL: LLM Agents Are Experiential Learners
  • Chen et al 2023 - FireAct: Toward Language Agent Fine-tuning Fine-tunes the LLM agent
  • CodeAct: Wang et al 2024 - Executable Code Actions Elicit Better LLM Agents
• AutoGPT: Yang et al 2023 - Auto-GPT for Online Decision Making: Benchmarks and Additional Opinions github
• Zhou et al 2023 - Agents: An Open-source Framework for Autonomous Language Agents
• Chen et al 2023 - Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models
• Wu et al 2025 - Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research
• OpenAI 2025 - Deep Research
• Yano et al 2025 - LaMDAgent: An Autonomous Framework for Post-Training Pipeline Optimization via LLM Agents
• Pham et al 2025 - Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems
• Wang et al 2026 - AI-NativeBench: An Open-Source White-Box Agentic Benchmark Suite for AI-Native Systems
• Tool Use and Agent Skills
  • “Agent Skills are instructions, scripts, and resources that agents can discover and use to do things more accurately and efficiently” (from here)
  • Claude - Agent Skills (I believe “agent skills” was introduced in Claude)
  • Agent Skills (website)
  • Li et al 2026 - SkillsBench: Benchmarking How Well Agent Skills Work Across Diverse Tasks
• Software Engineering (SWE) Agents
  • See also Software Engineering
  • Jimenez et al 2023 - SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
  • Yang et al 2024 - SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
  • Lindenbauer et al 2025 - From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents
• Web Agents
  • MiniWoB: Shi et al 2017 - World of Bits: An Open-Domain Platform for Web-Based Agents
  • MiniWoB++: Liu et al 2018 - Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration MiniWoB++
  • Zhou et al 2023 - WebArena: A Realistic Web Environment for Building Autonomous Agents
  • Koh et al 2024 - VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks
  • De Chezelles et al 2024 - The BrowserGym Ecosystem for Web Agent Research
• Mobile UI Agents
  • You et al 2024 - Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMs
• OS Agents
  • Wu et al 2024 - OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
  • Xie et al 2024 - OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
• AI, ML, CS
  • Tang et al 2023 - ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code
  • Chan et al 2024 - MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering (this is the highly cited one, see for example the GPT-5.6 Preview System Card)
  • Siegel et al 2024 - CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark

• Business
  • Bell et al 2026 - The Agentic AI Genome

• Overviews
  • Tran et al 2025 - Multi-Agent Collaboration Mechanisms: A Survey of LLMs

• Overviews
  • Sapkota et al 2025 - AI Agents vs. Agentic AI: A Conceptual taxonomy, applications and challenges v4 (better formatting)
• Papers
  • Zhu 2026 - The Internet of Agentic AI: Communication, Coordination, and Collective Intelligence at Scale

• Shunyu Yao website

• AI Singularity
• Computer Use Agents
• Dialog
• Language Model
• Prompting