2 papers
cs.CL2026
From Passive Response to Proactive Correction: Enhancing LLM Robustness Against Input Fact Perturbations
Ping Wang, Xiangguo Sun, Bingbing Xu +2
Large language models (LLMs) frequently produce confident yet factually incorrect responses when user inputs contain misleading premises, a phenomenon we attribute to fact perturba…
cs.NI2026
Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations
Yonas Kassa, James Bonacci, Ping Wang
The transformative potential of large language models (LLMs) in education, such as improving accessibility and personalized learning, is being eclipsed by significant challenges. T…