5 papers
SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories
Zhuoyun Yu, Xin Xie, Wuguannan Yao +4
Large language model (LLM) agents increasingly rely on reusable external skills to solve long-horizon interactive tasks. Existing training-free skill adaptation pipelines usually u…
SkillX: Automatically Constructing Skill Knowledge Bases for Agents
Chenxi Wang, Zhuoyun Yu, Xin Xie +8
Learning from experience is critical for building capable large language model (LLM) agents, yet prevailing self-evolving paradigms remain inefficient: agents learn in isolation, r…
What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations
Yujie Luo, Zhuoyun Yu, Xuehai Wang +6
Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate executable code, primarily due to in…
InnoGym: Benchmarking the Innovation Potential of AI Agents
Jintian Zhang, Kewei Xu, Jingsheng Zheng +10
LLMs and Agents have achieved impressive progress in code generation, mathematical reasoning, and scientific discovery. However, existing benchmarks primarily measure correctness,…
CellForge: Agentic Design of Virtual Cell Models
Xiangru Tang, Zhuoyun Yu, Jiapeng Chen +12
Virtual cell modeling aims to predict cellular responses to diverse perturbations but faces challenges from biological complexity, multimodal data heterogeneity, and the need for i…