Who cites «Can Language Models Solve Olympiad Programming?»
- s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
- DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligencearXiv:2406.11931DeepSeek-AI, Qihao Zhu, Daya Guo, et al.2024 · 196 citations
- KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
- From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
- CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo RatingsarXiv:2501.01257Shanghaoran Quan, Jiaxi Yang, Bowen Yu, et al.2025 · 37 citations
- Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?Annual Meeting of the Association for Computational Linguistics (ACL)Yancheng He, Shilong Li, Jiaheng Liu, et al.2025 · 30 citations
- Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Xingxuan Li, Weiwen Xu, Ruochen Zhao, et al.2025 · 13 citations
- rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified DatasetConference on Neural Information Processing Systems (NeurIPS)Yifei Liu, Li Lyna Zhang, Yi Zhu, et al.2025 · 8 citations
- Do LLMs Really Need 10+ Thoughts for “Find the Time 1000 Days Later”? Towards Structural Understanding of LLM OverthinkingAnnual Meeting of the Association for Computational Linguistics (ACL)Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou, et al.2026 · 4 citations
- Scaling Laws for Code: A More Data-Hungry RegimeAnnual Meeting of the Association for Computational Linguistics (ACL)Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.2026 · 3 citations
This page in Markdown → https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/cited-by/