从分布偏好角度切入，提出细粒度优化方法解决大模型遗忘问题，视角新颖。
arXiv:2510.04773v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) demonstrate remarkable capabilities learned from vast corpor…
注意力机制为LLM推理提供“预规划-锚定”节奏，突破强化学习的粗放信用分配，实现细粒度策略优化。
arXiv:2510.13554v2 Announce Type: replace-cross Abstract: The reasoning pattern of Large language models (LLMs) remains opaque, and reinforcement lear…
重新定义替换式LLM压缩的粒度，从层到子模块，为模型轻量化提供新视角。
arXiv:2606.02559v1 Announce Type: cross Abstract: Post-training compression of Large Language Models (LLMs) removes entire architectural components, e…