most citedAI Scientists for Building Virtual-Cell Models

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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,…

cs.CL2025

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…

cs.LG2025★ 3 cited

AI Scientists for Building Virtual-Cell Models

Xiangru Tang, Zhuoyun Yu, Jiapeng Chen +12

Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hypotheses. Whether they can go further…