论大语言模型强化学习训练中的 KL 正则化
论文标题：A COMEDY OF ESTIMATORS: ON KL REGULARIZATION IN RL TRAINING OF LLMS
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阿里新作 Let It Flow: Agentic Crafting on Rock and Roll 深度解读
论文标题：Building the ROME Model within an Open Agentic Learning Ecosystem
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DeepSeek 新作 mHC：为何要把超连接约束在流形上？
论文标题：mHC: Manifold-Constrained Hyper-Connections
论文链接：https://arxiv.org/pd
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字节 Seed 新作：通过辅助损失实现 MoE 专家与路由器的紧密耦合 (ERC Loss)
祝大家新年快乐～
论文标题：Coupling Experts and Routers in Mixture-of-Experts via an Auxi
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Bottom-up Policy Optimization: 自下而上的策略优化——语言模型内部潜藏的子策略
论文标题：Bottom-up Policy Optimization: Your Language Model Policy Secretly Cont
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Google DeepMind 新作：自回归模型中的涌现时间抽象实现了分层强化学习
论文标题：Emergent temporal abstractions in autoregressive models enable hierarch
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被牺牲的元认知：效率导向优化如何改变了模型的推理结构
论文标题：Schoenfeld’s Anatomy of Mathematical Reasoning by Language Models
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Who is Adam? 重新审视大模型 RLVR 阶段的优化器选择
博客标题：Who is Adam? SGD Might Be All We Need For RLVR In LLMs
博客链接：https://w
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代码大模型的 Scaling Laws：编程语言差异性与多语言混合策略研究
论文标题：Scaling Laws for Code: Every Programming Language Matters
论文链接：https:
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从 0.5B 到 72B：揭秘 RL Post-Training 中的计算、数据与模型规模权衡
论文标题：Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empir
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