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weitianxin/Awesome-Agentic-Reasoning

⭐ 1362 repository created 2025-08-31

Awesome Agentic Reasoning Papers is a curated research collection that accompanies the survey Agentic Reasoning for Large Language Models. It organizes work by thematic areas that integrate reasoning with action, spanning planning, tool use, search, self-evolution through memory and feedback, multi-agent systems, and real-world applications and benchmarks. The repository structures the field into three layers, each corresponding to a distinct reasoning paradigm under different environmental dynamics: foundational reasoning covering core single-agent abilities such as planning, tool-use optimization, and agentic search; self-evolving reasoning covering adaptation through feedback mechanisms, agentic memory, and evolving foundational capabilities; and collective reasoning covering multi-agent coordination, role taxonomy, collaboration and division of labor, and multi-agent memory and evolution. Across these layers it further distinguishes in-context reasoning, achieved through test-time scaling and structured orchestration, from post-training reasoning achieved through reinforcement learning and supervised fine-tuning. An applications section catalogs math and vibe-coding agents, scientific discovery, embodied agents, healthcare and medicine, and autonomous web exploration and research, and a benchmarks section indexes evaluations for tool use, search, memory and planning, multi-agent systems, and their applied domains. Each entry is presented in tables listing papers with links and publication years. The collection is an ongoing community effort that accepts pull requests and issue suggestions, and it points readers to the underlying arXiv survey and slides. It is aimed at researchers and practitioners who want a structured map of the agentic reasoning literature for large language models.

https://github.com/weitianxin/Awesome-Agentic-Reasoning

surveypapersagentic-reasoningllmresearchbenchmarks

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