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2025

两处容易踩的坑：LLM 消息数组与字典工具的隐藏副作用

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TRPO深度拆解：为什么做后训练应该读懂TRPO
COPO：基于认知模式的 Step-Level Agentic RL 优化
LLM 的下一步：从“会答”到“会想”——Planning as Data 与思考范式重构
探寻实时学习新路径：挖掘极致高效的“子空间微调”
RL新范式：从经验到更高质量数据——我们不再训练模型，而是在制造数据

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