让前沿AI老师互相竞技，再合作打造可验证课程，帮助学生超越模仿式学习。
arXiv:2607.08255v1 Announce Type: new Abstract: Large language models increasingly serve as teachers generating training data for smaller students. Pr…
提出多教师在线策略蒸馏框架，高效整合多个大模型能力，优于传统方法
arXiv:2606.30406v1 Announce Type: cross Abstract: Modern large language models (LLMs) rely on reinforcement learning during post-training to push spec…
多教师知识蒸馏为自动驾驶VLM减负，兼顾GPU内存与推理延迟。
arXiv:2601.21288v2 Announce Type: replace Abstract: Autonomous driving is an important and safety-critical task, and recent advances in LLMs/VLMs have…
多教师蒸馏新方法，通过反作用感知策略蒸馏实现通用能力恢复并保持领域特性，为模型微调与领域延续提供新思路。
arXiv:2605.27115v1 Announce Type: new Abstract: Domain specialization can improve LLM behavior in vertical domains, but often weakens the general capa…