--- title: "Chain-of-ThoughtsPapers vs ReAct" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/timothyxxx-chain-of-thoughtspapers-vs-ysymyth-react" tools: ["timothyxxx-chain-of-thoughtspapers", "ysymyth-react"] --- # Chain-of-ThoughtsPapers vs ReAct *GraphCanon updated Aug 17, 2026* ## Verdict Pick Chain-of-ThoughtsPapers if chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses; pick ReAct if reAct enhances large language models by improving reasoning and executing actions through specific tasks using GPT-3. [Chain-of-ThoughtsPapers](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers) reports 2.1k GitHub stars, 142 forks, and 0 open issues, last pushed Oct 5, 2023. [ReAct](https://github.com/ysymyth/ReAct) has 4.1k stars, 396 forks, and 5 open issues, last pushed Feb 6, 2024. Figures are from public GitHub metadata via [Chain-of-ThoughtsPapers's repository](https://github.com/Timothyxxx/Chain-of-ThoughtsPapers) and [ReAct's repository](https://github.com/ysymyth/ReAct). | | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | [ReAct](/tools/ysymyth-react.md) | | --- | --- | --- | | Tagline | A curated list of papers exploring chain-of-thought reasoning in large language models. | ReAct Prompting for decision-making with language models | | Stars | 2,104 | 4,109 | | Forks | 142 | 396 | | Open issues | 0 | 5 | | Language | - | Jupyter Notebook | | Adopt for | Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. | ReAct enhances large language models by improving reasoning and executing actions through specific tasks using GPT-3. | | Persona | end user agent | - | | Runtime | - | - | | License | - | MIT | | Categories | LLM Frameworks, Model Training | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Chain-of-ThoughtsPapers](/tools/timothyxxx-chain-of-thoughtspapers.md) | [ReAct](/tools/ysymyth-react.md) | | --- | --- | --- | | Maintenance | Archived (8%) | Dormant (18%) | | Days since push | 1036d | 923d | | Archived on GitHub | Yes | No | | Open issues (now) | 0 | 5 | | Stars delta | Unknown | +50 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/timothyxxx-chain-of-thoughtspapers/trust.md) | [trust report](/tools/ysymyth-react/trust.md) | ## Decision facts: Chain-of-ThoughtsPapers - **Adopt for:** Chain-of-ThoughtsPapers curates critical research on chain-of-thought reasoning in large language models, aimed at enhancing a model's ability to perform logical reasoning through iterative step-by-step analyses. - **Persona:** end user agent ## Decision facts: ReAct - **Adopt for:** ReAct enhances large language models by improving reasoning and executing actions through specific tasks using GPT-3. ## Choose when ### Choose Chain-of-ThoughtsPapers if… - Tags unique to Chain-of-ThoughtsPapers: chain-of-thought, codex, gpt-3, in-context-learning. - Also covers Model Training. - When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically. ### Choose ReAct if… - Tags unique to ReAct: decision-making, llm, prompting, reasoning. - Also covers AI Agents. - When aiming for better decision-making in HotpotQA, alfworld environments, or WebShop scenarios with GPT-3 ## When NOT to use Chain-of-ThoughtsPapers - If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. - This repository focuses on research and theoretical foundations, not ready-to-use software libraries or codebases, making it less suitable for projects that require immediate practical coding implementations. - In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a - what_is_missing ## When NOT to use ReAct - If requiring extensive custom task integration beyond provided notebooks, LangChain's zero-shot ReAct agent may be more preferable - When PaLM outperforms GPT-3 on specific tasks or if an alternative model is preferred ## Common questions ### What is the difference between Chain-of-ThoughtsPapers and ReAct? Chain-of-ThoughtsPapers: A curated list of papers exploring chain-of-thought reasoning in large language models.. ReAct: ReAct Prompting for decision-making with language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Chain-of-ThoughtsPapers over ReAct? Choose Chain-of-ThoughtsPapers over ReAct when Tags unique to Chain-of-ThoughtsPapers: chain-of-thought, codex, gpt-3, in-context-learning; Also covers Model Training; When you need insights into foundational and cutting-edge research on how language models can be prompted or structured to reason logically. ### When should I choose ReAct over Chain-of-ThoughtsPapers? Choose ReAct over Chain-of-ThoughtsPapers when Tags unique to ReAct: decision-making, llm, prompting, reasoning; Also covers AI Agents; When aiming for better decision-making in HotpotQA, alfworld environments, or WebShop scenarios with GPT-3. ### When should I avoid Chain-of-ThoughtsPapers? If your focus is on unrelated areas such as image processing or speech recognition, where chain-of-thought reasoning in LLMs does not directly play a role. This repository focuses on research and theoretical foundations, not ready-to-use software libraries or codebases, making it less suitable for projects that require immediate practical coding implementations. In scenarios necessitating alternative approaches to language model training which do not emphasize step-by-step reasoning, such as models trained purely for pattern recognition without emphasis on a what_is_missing ### When should I avoid ReAct? If requiring extensive custom task integration beyond provided notebooks, LangChain's zero-shot ReAct agent may be more preferable When PaLM outperforms GPT-3 on specific tasks or if an alternative model is preferred ### Is Chain-of-ThoughtsPapers or ReAct more popular on GitHub? ReAct has more GitHub stars (4,109 vs 2,104). Stars measure visibility, not whether either tool fits your constraints. ### Are Chain-of-ThoughtsPapers and ReAct open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Chain-of-ThoughtsPapers or ReAct? GraphCanon lists graph-backed alternatives at [Chain-of-ThoughtsPapers alternatives](/tools/timothyxxx-chain-of-thoughtspapers/alternatives) and [ReAct alternatives](/tools/ysymyth-react/alternatives) ([Chain-of-ThoughtsPapers markdown twin](/tools/timothyxxx-chain-of-thoughtspapers/alternatives.md), [ReAct markdown twin](/tools/ysymyth-react/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/timothyxxx-chain-of-thoughtspapers-vs-ysymyth-react.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Chain-of-ThoughtsPapers or ReAct? Chain-of-ThoughtsPapers: Archived. ReAct: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for Chain-of-ThoughtsPapers and ReAct? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Chain-of-ThoughtsPapers trust report](/tools/timothyxxx-chain-of-thoughtspapers/trust); [ReAct trust report](/tools/ysymyth-react/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=timothyxxx-chain-of-thoughtspapers`](/api/graphcanon/graph?tool=timothyxxx-chain-of-thoughtspapers) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_