collaborators

16 papers

cs.AI2026

ICAE-Bench: Evaluating Coding Agents as Interactive Project Builders

Zhongyuan Peng, Dan Huang, Chuyu Zhang +8

The recent emergence of vibe-coding workflows is changing what coding agents are expected to do. Instead of merely completing code under fully specified instructions, agents are in…

cs.AI2026

DailyReport: An Open-ended Benchmark for Evaluating Search Agents on Daily Search Tasks

Jingxuan Han, Wei Liu, Mingyang Zhu +8

Search Agents (SAs) typically leverage large language models (LLMs) to support complex information-seeking tasks by autonomously exploring web sources and synthesizing information…

cs.SE2026

Asuka-Bench: Benchmarking Code Agents on Underspecified User Intent and Multi-Round Refinement

Xin Wang, Liangtai Sun, Yaoming Zhu +8

Existing code-generation benchmarks score a single mapping from a complete prompt to a one-shot output. However, real web development is different. Users seldom write a full spec a…

cs.AI2026

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…

cs.AI2026

AgentEscapeBench: Evaluating Out-of-Domain Tool-Grounded Reasoning in LLM Agents

Zhengkang Guo, Yiyang Li, Lin Qiu +7

As LLM-based agents increasingly rely on external tools, it is important to evaluate their ability to sustain tool-grounded reasoning beyond familiar workflows and short-range inte…

cs.SE2026

SWE-Cycle: Benchmarking Code Agents across the Complete Issue Resolution Cycle

Hao Guan, Lingyue Fu, Shao Zhang +8

As autonomous code agents move toward end-to-end software development, evaluating their practical autonomy becomes critical. Current benchmarks hide friction by testing agents in p…