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English(EN) Post-Training Language Models for Gold-Medal Performance in Coding Competitions

AI模型在编码竞赛中取得金牌表现,超越顶尖人类选手

研究人员开发了一个专门的流程来训练大型语言模型进行竞争性编程,在诸如国际信息学奥林匹克竞赛(IOI)和国际大学生程序设计竞赛(ICPC)等挑战性国际竞赛中取得了金牌表现。通过结合精选的问题、合成推理轨迹、监督微调和强化学习,他们训练了Nemotron-3-Nano-CC和Nemotron-3-Ultra-CC等模型。他们的GenCorrect策略在测试时进一步优化了解决方案,使AI系统在IOI 2026中超越了顶尖人类分数,标志着一个重要的里程碑。 AI

影响 为AI在复杂问题解决中的推理能力设定了新的基准,可能影响未来AI在逻辑和策略方面的发展。

排序理由 该集群报道了一篇已发表的学术论文,详细介绍了一种训练AI模型进行竞争性编程的新方法。

在 arXiv cs.AI 阅读 →

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AI模型在编码竞赛中取得金牌表现,超越顶尖人类选手

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该集群报道了一篇已发表的学术论文,详细介绍了一种训练AI模型进行竞争性编程的新方法。
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报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Aleksander Ficek, Sean Narenthiran, Mehrzad Samadi, Somshubra Majumdar, Boris Ginsburg ·

    训练后语言模型在编程竞赛中获得金牌表现

    arXiv:2609.02849v1 Announce Type: cross Abstract: Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its most challenging settings. We present an end-to-end specialization pipeline com…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Boris Ginsburg ·

    用于编码竞赛金牌表现的训练后语言模型

    Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its most challenging settings. We present an end-to-end specialization pipeline combining large-scale problem curation, synthetic rea…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    用于编码竞赛金牌表现的训练后语言模型

    A specialization pipeline combining curated problems, synthetic reasoning, supervised fine-tuning, and reinforcement learning trains competitive programming models that exceed top human scores on IOI benchmarks using iterative test-time refinement.