4 papers
Compile Away Uncertainty: Self-Evolving Agent Skills via Programmatic Compilation
Chengyu Yang, Yunxiang Zheng, Zongzheng Li +6
Self-evolving agent skills enable AI agents to accumulate and refine reusable procedural knowledge from interaction experience without updating model parameters. However, since suc…
FedSkillGit: Federated Skill Evolution via Version Control
Boxun Lan, Jiamei Li, Weijian Li +5
Large language model agents can improve their capabilities by evolving reusable natural-language skills from execution experience. In real-world deployments, this experience is dis…
FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning
Jiajun Cao, Qizhe Zhang, Peidong Jia +11
Vision-Language-Action (VLA) models have demonstrated significant potential in complex scene understanding and action reasoning, leading to their increasing adoption in end-to-end…
Improving Retrospective Language Agents via Joint Policy Gradient Optimization
Xueyang Feng, Bo Lan, Quanyu Dai +5
In recent research advancements within the community, large language models (LLMs) have sparked great interest in creating autonomous agents. However, current prompt-based agents o…