{"data":{"slug":"atfortes-awesome-llm-reasoning","name":"Awesome-LLM-Reasoning","tagline":"Compiles resources on chain-of-thought prompting to advanced reasoning systems like OpenAI o1 and DeepSeek-R1.","github_url":"https://github.com/atfortes/Awesome-LLM-Reasoning","owner":"atfortes","repo":"Awesome-LLM-Reasoning","owner_avatar_url":"https://avatars.githubusercontent.com/u/57639145?v=4","primary_language":null,"stars":3685,"forks":213,"topics":["awesome","chain-of-thought","chatgpt","cot","deepseek","deepseek-r1","gpt","gpt-4o","in-context-learning","language-models","mllm","multimodal","openai-o1","papers","prompt","prompt-engineering","reasoning","strawberry"],"archived":false,"github_pushed_at":"2026-04-20T00:57:27+00:00","maintenance_label":"Slowing","stars_delta_30d":28,"url":"https://www.graphcanon.com/tools/atfortes-awesome-llm-reasoning","markdown_url":"https://www.graphcanon.com/tools/atfortes-awesome-llm-reasoning.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/atfortes-awesome-llm-reasoning","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=atfortes-awesome-llm-reasoning","description":"From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓","homepage_url":null,"license":"MIT","open_issues":27,"watchers":45,"ai_summary":"Covers chain-of-thought methods, prompt engineering, multimodal learning, in-context reasoning capabilities in language-models. Includes references to research papers and specific models from OpenAI GPT series and DeepSeek.","readme_excerpt":"\n\n
\n \"Stargazers\"\n \"Forks\"\n \"Contributors\"\n \"MIT\n
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Awesome LLM Reasoning

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\n Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.\n

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\n 🗂️ Table of Contents\n
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  1. Survey
    2. \n
  2. Analysis
    3. \n
  3. Technique\n \n
    4. \n
  4. Other Useful Resources
    5. \n
  5. Other Awesome Lists
    6. \n
  6. Contributing
    7. \n
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\n\nIf you would like to test the symbolic reasoning ability of LLMs, take a look at: LLMSymbolicReasoningBench 😄\n\n\n\n## Survey\n\n### 2025\n\n1. **[Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey.](https://arxiv.org/abs/2503.12605)** [[code](https://github.com/yaotingwangofficial/Awesome-MCoT)]\n\n *Yaoting Wang, Shengqiong Wu, Yuecheng Zhang, William Wang, Ziwei Liu, Jiebo Luo, Hao Fei.* Preprint'25\n\n2. **[Recent Advances in Large Language Model Benchmarks Against Data Contamination: From Static to Dynamic Evaluation.](https://arxiv.org/abs/2502.17521)** [[code](https://github.com/SeekingDream/Static-to-Dynamic-LLMEval)]\n\n *Simin Chen, Yiming Chen, Zexin Li, Yifan Jiang, Zhongwei Wan, Yixin He, Dezhi Ran, Tianle Gu, Haizhou Li, Tao Xie, Baishakhi Ray.* Preprint'25\n\n### 2024\n\n1. **[Attention Heads of Large Language Models: A Survey.](https://arxiv.org/abs/2409.03752)** [[code](https://github.com/IAAR-Shanghai/Awesome-Attention-Heads)]\n\n *Zifan Zheng, Yezhaohui Wang, Yuxin Huang, Shichao Song, Bo Tang, Feiyu Xiong, Zhiyu Li.* Preprint'24\n\n1. **[Internal Consistency and Self-Feedback in Large Language Models: A Survey.](https://arxiv.org/abs/2407.14507)** [[code](https://github.com/IAAR-Shanghai/ICSFSurvey)]\n\n *Xun Liang, Shichao Song, Zifan Zheng, Hanyu Wang, Qingchen Yu, Xunkai Li, Rong-Hua Li, Feiyu Xiong, Zhiyu Li.* Preprint'24\n\n1. **[Puzzle Solving using Reasoning of Large Language Models: A Survey.](https://arxiv.org/abs/2402.11291)** [[code](https://puzzlellms.github.io/)]\n\n *Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, Giorgos Stamou.* Preprint'24\n\n1. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges.](https://arxiv.org/abs/2402.00157)** \n\n *Janice Ahn, Rishu Verma, Renze Lou, Di Liu, Rui Zhang, Wenpeng Yin.* ACL'24\n\n### 2022\n\n1. **[Towards Reasoning in Large Language Models: A Survey.](https://arxiv.org/abs/2212.10403)** [[code](https://github.com/jeffhj/LM-reasoning)]\n\n *Jie Huang, Kevin Chen-Chuan Chang.* ACL'23 Findings\n\n1. **[Reasoning with Language Model Promp","github_created_at":"2022-11-05T08:03:53+00:00","created_at":"2026-07-11T10:31:44.223816+00:00","updated_at":"2026-09-20T06:53:02.583751+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"chain-of-thought","name":"chain-of-thought"},{"slug":"chatgpt","name":"chatgpt"},{"slug":"cot","name":"cot"},{"slug":"deepseek-r1","name":"deepseek-r1"},{"slug":"gpt-4o","name":"gpt-4o"},{"slug":"in-context-learning","name":"in-context-learning"},{"slug":"language-models","name":"language models"},{"slug":"prompt-engineering","name":"prompt-engineering"}],"trust":{"provenance":{"is_fork":false,"github_id":562071276,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T06:53:00.942Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":153,"last_release_at":null,"stars_delta_30d":28,"open_issues_delta_30d":1},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:57:51.414Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T06:53:02.010Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T06:53:02.010Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Freely available under the MIT license; 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