--- title: "Who cites Competitive Programming with — 62 citing papers" description: "62 papers of the Elamur Research library cite «Competitive Programming with Large Reasoning Models», found in their bibliographies; the…" canonical: "https://research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Competitive Programming with Large Reasoning…](https://md.research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/) / cited by # Who cites «Competitive Programming with Large Reasoning Models» 62 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← back to «Competitive Programming with Large Reasoning Models»](https://md.research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/) 1. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations* 2. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/) 3. [**ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning arXiv:2504.01296**Bairu Hou, Yang Zhang, Jiabao Ji, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-thinkprune-pruning-long-chain-thought/) 4. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations* 5. **[RARE: Retrieval-Augmented Reasoning Enhancement for Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2025-rare-retrieval-augmented-reasoning-enhancement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hieu Tran, Zonghai Yao, Zhichao Yang, et al.*2025 · 20 citations* 6. **[The Role of Deductive and Inductive Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/cai-2025-role-deductive-inductive-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengkun Cai, Xu Zhao, Haoliang Liu, et al.*2025 · 17 citations* 7. **[Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQL](https://md.research.elamur.ai/free/en/papers/yao-2026-arctic-text2sql-r1-simple-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhewei Yao, Guoheng Sun, Łukasz Borchmann, et al.*2026 · 15 citations* 8. [**QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning arXiv:2505.17667**Fanqi Wan, Weizhou Shen, Shengyi Liao, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-qwenlong-l1-long-context/) 9. **[ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2025-reasonmed-370k-multi-agent-generated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Sun, Xingyu Qian, Weiwen Xu, et al.*2025 · 11 citations* 10. **[Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models](https://md.research.elamur.ai/free/en/papers/xuan-2025-seeing-is-believing-but-how/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.*2025 · 11 citations* 11. **[Thinking Out Loud: Do Reasoning Models Know When They're Right?](https://md.research.elamur.ai/free/en/papers/zeng-2025-thinking-out-loud-do-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingcheng Zeng, Weihao Xuan, Leyang Cui, et al.*2025 · 9 citations* 12. **[PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning](https://md.research.elamur.ai/free/en/papers/hu-2026-pacore-learning-scale-test-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingcheng Hu, Yinmin Zhang, Shijie Shang, et al.*2026 · 5 citations* 13. **[Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations* 14. **[Scaling Laws for Code: A More Data-Hungry Regime](https://md.research.elamur.ai/free/en/papers/luo-2026-scaling-laws-code-more-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.*2026 · 3 citations* 15. **[Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight Models](https://md.research.elamur.ai/free/en/papers/samadi-2026-scaling-test-time-compute-achieve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran, et al.*2026 · 1 citation* 16. **[Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition](https://md.research.elamur.ai/free/en/papers/zheng-2026-market-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushuo Zheng, Huiyu Duan, Zicheng Zhang, et al.*2026* 17. **[MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification Enhancement](https://md.research.elamur.ai/free/en/papers/xu-2026-mavencoder-competitive-code-generation-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZhenChun Xu, Yi Cai, Dajun Zheng, et al.*2026* 18. **[ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework](https://md.research.elamur.ai/free/en/papers/qin-2026-reflectrm-boosting-generative-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Qin, Liangxin Liu, Yu Liang, et al.*2026* 19. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026* 20. **[Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-self-guided-alignment-adaptive-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Wang, Zhanyang Liu, Taotao Zhou, et al.*2026* 21. **[SwissGov-RSD: A Human-annotated, Cross-lingual Benchmark for Token-level Recognition of Semantic Differences Between Related Documents](https://md.research.elamur.ai/free/en/papers/wastl-2026-swissgov-rsd-human-annotated-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michelle Wastl, Jannis Vamvas, Rico Sennrich*2026* 41 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/el-kishky-2025-competitive-programming-large-reasoning-models/) — Competitive Programming with Large Reasoning Models