4 papers
SAGE: A Quantitative Evaluation of Socialized Evolution in Agent Ecosystems
Linyue Pan, Yaoming Zhu, Lin Qiu +2
Self-improving language agents are typically evaluated in isolation: an agent attempts a task, receives feedback, and iteratively refines its own behavior. Yet agents increasingly…
Natural-Language Agent Harnesses
Linyue Pan, Lexiao Zou, Shuo Guo +2
Agent performance is strongly shaped by the surrounding harness: the external execution system around a model that organizes a task run. Yet this logic is usually buried in tightly…
CATArena: Evaluating Evolutionary Capabilities of Code Agents via Iterative Tournaments
Lingyue Fu, Xin Ding, Linyue Pan +9
Current evaluation for Large Language Model (LLM) code agents predominantly focus on generating functional code in single-turn scenarios, which fails to evaluate the agent's capabi…
EvoConfig: Self-Evolving Multi-Agent Systems for Efficient Autonomous Environment Configuration
Xinshuai Guo, Jiayi Kuang, Linyue Pan +6
A reliable executable environment is the foundation for ensuring that large language models solve software engineering tasks. Due to the complex and tedious construction process, l…