---
title: "Who cites Kaya Stechly — 109 papers of our library"
description: "109 papers of the Elamur Research library cite the works of Kaya Stechly, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/kaya-stechly/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kaya-stechly/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Kaya Stechly](https://md.research.elamur.ai/free/en/authors/kaya-stechly/) / cited by

# Who cites Kaya Stechly

116 citations of their works from 109 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Kaya Stechly](https://md.research.elamur.ai/free/en/authors/kaya-stechly/)

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. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
3. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
4. [**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/)
5. **[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*
6. **[TheAgentCompany: Benchmarking LLM Agents on Consequential Real World Tasks](https://md.research.elamur.ai/free/en/papers/xu-2024-theagentcompany-benchmarking-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Frank F. Xu, Yufan Song, Boxuan Li, et al.*2024 · 68 citations*
7. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
8. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/)
9. [**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/)
10. [**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/)
11. **[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*
12. [**On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks arXiv:2402.08115**Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/stechly-2024-self-verification-limitations-large-language/)
13. [**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/)
14. [**LLM4SR: A Survey on Large Language Models for Scientific Research arXiv:2501.04306**Ziming Luo, Zonglin Yang, Zexin Xu, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/luo-2025-llm4sr-survey-large-language/)
15. [**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/)
16. **[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*
17. **[SemEval-2026 Task 11: Disentangling Content and Formal Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/valentino-2026-semeval-2026-task-11-disentangling/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Marco Valentino, Leonardo Ranaldi, Giulia Pucci, et al.*2026 · 22 citations*
18. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
19. [**The Limits of Inference Scaling Through Resampling arXiv:2411.17501**Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/stroebl-2024-limits-inference-scaling-through-resampling/)
20. **[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*
21. **[Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools](https://md.research.elamur.ai/free/en/papers/hao-2025-large-language-models-can-solve/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yilun Hao, Yongchao Chen, Yang Zhang, et al.*2025 · 18 citations*
22. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mihir Parmar, Xin Liu, Palash Goyal, et al.*2025 · 16 citations*
23. [**Data-driven Discovery with Large Generative Models arXiv:2402.13610**Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2024-data-driven-discovery-large-generative/)
24. [**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/)
25. **[Problem Solving Through Human–AI Preference-based Cooperation](https://md.research.elamur.ai/free/en/papers/dutta-2025-problem-solving-through-human-ai/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.*2025 · 9 citations*
26. **[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*
27. **[Analysing Chain of Thought Dynamics: Active Guidance or Unfaithful Post-hoc Rationalisation?](https://md.research.elamur.ai/free/en/papers/lim-2025-analysing-chain-thought-dynamics-active/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel Lewis-Lim, Xingwei Tan, Zhixue Zhao, et al.*2025 · 5 citations*
28. [**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/)
29. **[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*
30. **[AOT*: Efficient Synthesis Planning via LLM-Empowered AND-OR Tree Search](https://md.research.elamur.ai/free/en/papers/song-2026-aot-efficient-synthesis-planning-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaozhuang Song, Xuanhao Pan, Xinjian Zhao, et al.*2026 · 2 citations*
31. **[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*
32. **[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*
33. **[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*
34. [**Integrating Neural and Symbolic Components in a Model of Pragmatic Question-Answering**Polina Tsvilodub, Robert D. Hawkins, Michael Franke*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2025-integrating-neural-symbolic-components-model/)
35. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
36. **[CARL: Constraint-Aware Reinforcement Learning for Planning with LLMs](https://md.research.elamur.ai/free/en/papers/qi-2026-carl-constraint-aware-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiuyi Qi, Jinjian Zhang, Mutian Bao, et al.*2026*
37. [**Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives arXiv:2607.18443**Polina Tsvilodub, Fausto Carcassi, Michael Franke*2026*](https://md.research.elamur.ai/free/en/papers/tsvilodub-2026-computational-models-pragmatic-reasoning-flexible/)
38. **[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*

71 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/kaya-stechly/) — Kaya Stechly