Showing cs.AIShow all
3 papers · 1 filter
cs.AI2026
EvoProbe: Evaluation-Driven Benchmark Evolution for LLM Agents
Qianhong Guo, Wei Xie, Xiaofang Cai +3
Static benchmarks for large language model (LLM) agents face saturation and data contamination risks, motivating continual updates to evaluation tasks. However, aggregate scores an…
cs.AI2026
Phantom Merge: When Your Large Language Model Agents Pick One but Tell You About Another
Wangshu Zhu, Qianwen Guo, Yushun Dong
LLM agents increasingly operate over multiple entities, where reliable response generation requires not only retrieving relevant evidence but also preserving its association with t…
cs.AI2025
League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models
Qianhong Guo, Wei Xie, Xiaofang Cai +7
Although large language models (LLMs) have shown exceptional capabilities across a wide range of tasks, reliable evaluation remains a critical challenge due to data contamination,…