4 citations · 5 across the 15 of their papers we have counts for
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cs.AI2026
AgentPerturb: Evaluating LLM Agent Robustness under Controlled Interaction Perturbations
Yuanjian Xu, Jinyi Han, Jianing Hao +5
Real-world tasks are often complex and noisy, posing substantial challenges for LLM agents. Yet existing evaluations lack a systematic framework for jointly characterizing potentia…
cs.AI2026
TRAJDEBUG: Tracing Error Lifecycle to Identify Critical Failures in Long-Horizon Agent Trajectories
Yunjia Qi, Zehua Yin, Xintong Shi +10
LLM-based agentic systems have shown remarkable capabilities in complex domains, while suffering from cascading errors and difficulty in debugging. Critical error detection aims to…
cs.AI2025★ 1 cited
Overconfidence in LLM-as-a-Judge: Diagnosis and Confidence-Driven Solution
Zailong Tian, Zhuoheng Han, Yanzhe Chen +5
Large Language Models (LLMs) are widely used as automated judges, where practical value depends on both accuracy and trustworthy, risk-aware judgments. Existing approaches predomin…