collaborators

16 papers

cs.CL2026

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

Qing Zong, Jiayu Liu, Junhao Shen +9

Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, such as fixed tasks and feedb…

cs.SE2026

Rethinking Self-Evolving Agent Skills: Feedback Dynamics over Multiple Rounds

Yuxuan Liu, Zhaochen Su, Yuhao Zhang +9

Self-evolving skill systems promise to improve agents by turning execution feedback into persistent skill updates without changing the underlying model. Yet it remains unclear when…

cs.AI2026

MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning

Kawai Chung, Chunkit Chan, Yauwai Yim +12

The paper introduces MultivationBench, a benchmark that tests multimodal large language models on their ability to reason about evolving human motivations across sequential visual…

cs.CL2026

EvolvingWorld: An Open-Schema Framework for Co-Evolving Role-Play Agents and World Model in Interactive Literary World

Qing Zong, Yue Guo, Mengxin Yang +2

This paper introduces EvolvingWorld, a framework and benchmark for character and world co-evolution in interactive literary worlds. Existing systems either treat interactive litera…

cs.CL2026

UNIBROWSE: A Data-to-Agent Framework for Multimodal BrowseComp

Xiyu Wei, Qingwei Zong, Zhuocheng Yu +1

Multimodal BrowseComp tasks require agents to combine perception, tool use, and long-horizon reasoning over dynamic web content, challenging their ability to handle compositional s…

cs.AI2026

CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents

Jiayu Liu, Cheng Qian, Zhaochen Su +4

Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability. This neglects a crucial capabi…