🔗 Who cites «Stream of Search (SoS): Learning to Search in Language»

47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 26 with a page here, the most cited first · ← back to «Stream of Search (SoS): Learning to Search in Language»

1. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
2. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
3. From System 1 to System 2: A Survey of Reasoning Large Language ModelsarXiv:2502.17419Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.2025 · 165 citations
4. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
5. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
6. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
7. Recursive Introspection: Teaching Language Model Agents How to Self-ImproveConference on Neural Information Processing Systems (NeurIPS)Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.2024 · 75 citations
8. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
9. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
10. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
11. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
12. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-ThoughtarXiv:2501.04682Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.2025 · 47 citations
13. Towards Thinking-Optimal Scaling of Test-Time Compute for LLM ReasoningConference on Neural Information Processing Systems (NeurIPS)Wenkai Yang, Shuming Ma, Yankai Lin, et al.2025 · 43 citations
14. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
15. Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM ReasoningarXiv:2506.06632Shubham Parashar, Shurui Gui, Xiner Li, et al.2025 · 23 citations
16. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
17. Mastering Board Games by External and Internal Planning with Language ModelsarXiv:2412.12119John Schultz, Jakub Adamek, Matej Jusup, et al.2024 · 14 citations
18. Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsYuan Sui, Yufei He, Tri Cao, et al.2026 · 13 citations
19. Satori: Reinforcement Learning with Chain-of-Action-Thought Enhances LLM Reasoning via Autoregressive SearcharXiv:2502.02508Maohao Shen, Guangtao Zeng, Zhenting Qi, et al.2025 · 13 citations
20. EVOLvE: Evaluating and Optimizing LLMs For In-Context ExplorationarXiv:2410.06238Allen Nie, Yi Su, Bo Chang, et al.2024 · 9 citations
21. Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation ModelsarXiv:2405.15143Cong Lu, Shengran Hu, Jeff Clune2024 · 7 citations
22. Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and DistillationarXiv:2502.01694Juno Kim, Denny Wu, Jason Lee, et al.2025 · 6 citations
23. BoxingGym: Benchmarking Progress in Automated Experimental Design and Model DiscoveryarXiv:2501.01540Kanishk Gandhi, Michael Y. Li, Lyle Goodyear, et al.2025 · 4 citations
24. Quantifying the Impact of Structured Output Format on Large Language Models through Causal InferenceFindings of the Association for Computational LinguisticsHan Yuan, Yue Zhao, Li Zhang, et al.2026 · 2 citations
25. Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse DomainsAnnual Meeting of the Association for Computational Linguistics (ACL)Yi Su, Dian Yu, Linfeng Song, et al.2026
26. GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy InputsFindings of the Association for Computational LinguisticsZhengxin Zhang, Chengyu Huang, Xufu Liu, et al.2026

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