--- title: "Who cites On the Self-Verification — 39 citing papers" description: "39 papers of the Elamur Research library cite «On the Self-Verification Limitations of Large Language Models on Reasoning and Planning…" canonical: "https://research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [On the Self-Verification Limitations of Large…](https://md.research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/) / cited by # Who cites «On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks» 39 papers of our library cite it (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← back to «On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks»](https://md.research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/) 1. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/) 2. [**LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks arXiv:2402.01817 · Proceedings of the 41 st International Conference on Machine Learning, Vienna, Austria. PMLR 235, 2024**Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, et al.*2024 · 88 citations*](https://md.research.elamur.ai/free/en/papers/kambhampati-2024-llms-t-plan-but-help/) 3. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations* 4. [**Formal Mathematical Reasoning: A New Frontier in AI arXiv:2412.16075**Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-formal-mathematical-reasoning-new-frontier/) 5. [**Stream of Search (SoS): Learning to Search in Language arXiv:2404.03683**Kanishk Gandhi, Denise Lee, Gabriel Grand, et al.*2024 · 49 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2024-stream-search-sos-learning-search/) 6. **[The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning](https://md.research.elamur.ai/free/en/papers/agarwal-2025-unreasonable-effectiveness-entropy-minimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shivam Agarwal, Zimin Zhang, Lifan Yuan, et al.*2025 · 47 citations* 7. [**A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic Systems arXiv:2504.09037**Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/ke-2025-survey-frontiers-llm-reasoning-inference/) 8. [**Gold-medalist Performance in Solving Olympiad Geometry with AlphaGeometry2 arXiv:2502.03544**Yuri Chervonyi, Trieu H. Trinh, Miroslav Olšák, et al.*2025 · 31 citations*](https://md.research.elamur.ai/free/en/papers/chervonyi-2025-gold-medalist-performance-solving-olympiad/) 9. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations* 10. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations* 11. [**Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs arXiv:2506.19923**Kaito Baba, Chaoran Liu, Shuhei Kurita, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/baba-2025-prover-agent-agent-based-framework/) 12. **[DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints](https://md.research.elamur.ai/free/en/papers/zhang-2026-deepplanning-benchmarking-long-horizon-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinger Zhang, Shutong Jiang, Renhao Li, et al.*2026 · 5 citations* 13. [**Evaluating the Systematic Reasoning Abilities of Large Language Models through Graph Coloring arXiv:2502.07087**Alex Heyman, Joel Zylberberg*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/heyman-2025-evaluating-systematic-reasoning-abilities-large/) 14. **[DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-deeppresenter-environment-grounded-reflection-agentic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Zheng, Guozhao Mo, Xinru Yan, et al.*2026 · 3 citations* 15. **[Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math](https://md.research.elamur.ai/free/en/papers/pandit-2026-hard2verify-step-level-verification-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.*2026 · 2 citations* 16. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation* 17. **[Verification-Aware Planning for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/xu-2026-verification-aware-planning-multi-agent/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tianyang Xu, Dan Zhang, Kushan Mitra, et al.*2026 · 1 citation* 18. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026* 21 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/) — On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks