这篇新论文提出强化学习感知的知识蒸馏，让教师模型“教”学生时更关注推理过程，突破传统蒸馏只传答案的局限。
arXiv:2602.22495v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) post-training has recently driven major gains in long chain-of-t…
用Interaction Tensor框架深挖知识蒸馏中学生模型的特征学习机制，揭示黑暗知识的秘密。
arXiv:2606.03052v1 Announce Type: new Abstract: Knowledge Distillation (KD) is a powerful tool for model compression, yet the precise mechanisms by wh…
颠覆认知？弱教师模型也能有效蒸馏LLM，预训练阶段教师强度并非关键。
arXiv:2605.23857v1 Announce Type: new Abstract: Knowledge distillation generally assumes a strong-to-weak relationship where stronger teachers yield b…
无需辅助组件的投影引导跨分词器知识蒸馏，有效解决词汇不兼容问题。
arXiv:2605.21699v1 Announce Type: cross Abstract: Cross-tokenizer knowledge distillation allows a student model to learn from teachers with incompatib…
看点在通过回溯机制缓解LLM推理蒸馏中的双重暴露偏差，提升长链思维迁移效率
arXiv:2605.19433v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chai…