针对LLM后训练安全对齐，提出基于轨迹的安全补丁学习方法，提升模型对齐的可靠性与鲁棒性。
arXiv:2607.16242v1 Announce Type: cross Abstract: Fine-Tuning-as-a-Service (FTaaS) platforms let users train large language models (LLMs) on customize…
LLM推理训练新突破：通过训练时分解攻克零奖励难题，让模型从失败轨迹中学习！
arXiv:2606.09883v1 Announce Type: cross Abstract: Large language models (LLMs) have made remarkable progress in reasoning tasks, largely driven by pos…
从智能体轨迹中提炼可迁移技能，提出一种基于局部经验的知识蒸馏新方法，助力通用智能体学习。
arXiv:2603.25158v5 Announce Type: replace Abstract: Large Language Model (LLM) agents increasingly rely on domain-specific skills, yet manually author…
让LLM智能体从历史轨迹中自动学习并自适应重构技能，提升任务泛化能力。
arXiv:2606.01311v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on reusable external skills to solve long-horizo…