--- title: "Who cites STaR: Bootstrapping Reasoning With Reasoning" description: "585 papers of the Elamur Research library cite «STaR: Bootstrapping Reasoning With Reasoning», found in their bibliographies · page 1 of 3; the most…" canonical: "https://research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [STaR: Bootstrapping Reasoning With Reasoning](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/) / cited by # Who cites «STaR: Bootstrapping Reasoning With Reasoning» 585 papers of our library cite it (of the 140884 whose bibliographies we read) · 64 with a page here, the most cited first · page 1 of 3 · [← the paper](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/) **1** [2](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/2/) - [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/) — Jason Wei, Xuezhi Wang, Dale Schuurmans, et al. · 2022 · 11 278 citations - [DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deepseek-2025-ai-deepseek-r1-incentivizing-reasoning-capability/) — DeepSeek-AI, Daya Guo, Dejian Yang, et al. · 2025 · 4 593 citations - [Large language models are zero-shot reasoners](https://md.research.elamur.ai/free/en/papers/kojima-2022-large-language-models-zero-shot/) — Takeshi Kojima, Shixiang Shane Gu, Machel Reid, et al. · 2022 · 3 780 citations - [ReAct: Synergizing Reasoning and Acting in Language Models](https://md.research.elamur.ai/free/en/papers/yao-2022-react-synergizing-reasoning-acting-language/) — Shunyu Yao, Jeffrey Zhao, Dian Yu, et al. · 2022 · 2 493 citations - [Scaling Instruction-Finetuned Language Models](https://md.research.elamur.ai/free/en/papers/chung-2022-scaling-instruction-finetuned-language-models/) — Hyung Won Chung, Le Hou, Shayne Longpre, et al. · 2022 · 2 176 citations - [Toolformer: Language Models Can Teach Themselves to Use Tools](https://md.research.elamur.ai/free/en/papers/schick-2023-toolformer-language-models-can-teach/) — Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, et al. · 2023 · 2 020 citations - [Let's Verify Step by Step](https://md.research.elamur.ai/free/en/papers/lightman-2023-let-s-verify-step-step/) — Hunter Lightman, Vineet Kosaraju, Yura Burda, et al. · 2023 · 1 359 citations - [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/) — Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al. · 2023 · 866 citations - [Is ChatGPT a General-Purpose Natural Language Processing Task Solver?](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/) — Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al. · 2023 · 818 citations - [Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) — Jie Huang, Kevin Chen-Chuan Chang · 2023 · 775 citations - [CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/) — Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al. · 2023 · 689 citations - [Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes](https://md.research.elamur.ai/free/en/papers/hsieh-2023-distilling-step-step-outperforming-larger/) — Cheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al. · 2023 · 684 citations - [Large Language Models Are Human-Level Prompt Engineers](https://md.research.elamur.ai/free/en/papers/zhou-2022-large-language-models-human-level/) — Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al. · 2022 · 677 citations - [s1: Simple test-time scaling](https://md.research.elamur.ai/free/en/papers/muennighoff-2025-s1-simple-test-time-scaling/) — Niklas Muennighoff, Zitong Yang, Weijia Shi, et al. · 2025 · 584 citations - [Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting](https://md.research.elamur.ai/free/en/papers/turpin-2023-language-models-don-t-always/) — Miles Turpin, Julian Michael, Ethan Perez, et al. · 2023 · 568 citations - [Improving Factuality and Reasoning in Language Models through Multiagent Debate](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/) — Yilun Du, Shuang Li, Antonio Torralba, et al. · 2023 · 564 citations - [Large Language Models Can Self-Improve](https://md.research.elamur.ai/free/en/papers/huang-2023-large-language-models-can-self/) — Jiaxin Huang, Shixiang Gu, Le Hou, et al. · 2023 · 560 citations - [Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/) — Charlie Snell, Jaehoon Lee, Kelvin Xu, et al. · 2024 · 524 citations - [Tulu 3: Pushing Frontiers in Open Language Model Post-Training](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/) — Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al. · 2024 · 379 citations - [WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/) — Haipeng Luo, Qingfeng Sun, Can Xu, et al. · 2023 · 366 citations - [Solving math word problems with process- and outcome-based feedback](https://md.research.elamur.ai/free/en/papers/uesato-2022-solving-math-word-problems-process/) — Jonathan Uesato, Nate Kushman, Ramana Kumar, et al. · 2022 · 334 citations - [Kimi K2: Open Agentic Intelligence](https://md.research.elamur.ai/free/en/papers/kimi-2025-team-kimi-k2-open-agentic/) — Kimi Team, Yifan Bai, Yiping Bao, et al. · 2025 · 331 citations - [Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models](https://md.research.elamur.ai/free/en/papers/wu-2023-visual-chatgpt-talking-drawing-editing/) — Chenfei Wu, Shengming Yin, Weizhen Qi, et al. · 2023 · 315 citations - [Challenges and Applications of Large Language Models](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/) — Jean Kaddour, Joshua Harris, Maximilian Mozes, et al. · 2023 · 300 citations - [Can language models learn from explanations in context?](https://md.research.elamur.ai/free/en/papers/lampinen-2022-can-language-models-learn-explanations/) — Andrew Lampinen, Ishita Dasgupta, Stephanie Chan, et al. · 2022 · 288 citations **1** [2](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/2/) [3](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/3/) [next →](https://md.research.elamur.ai/free/en/papers/zelikman-2022-star-bootstrapping-reasoning-reasoning/cited-by/page/2/)