Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments
Yuquan Wang, Mi Zhang, Yining Wang +4
Large Reasoning Models (LRMs) have demonstrated impressive performance in reasoning-intensive tasks, but they remain vulnerable to harmful content generation, particularly in the m…
cs.CL2026
From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models
Wenxuan Li, Zhenfei Zhang, Mi Zhang +4
Large language models (LLMs) may memorize sensitive or copyrighted content, raising significant privacy and legal concerns. While machine unlearning has emerged as a potential reme…
cs.CL2025
The Illusionist's Prompt: Exposing the Factual Vulnerabilities of Large Language Models with Linguistic Nuances
Yining Wang, Yuquan Wang, Xi Li +3
As Large Language Models (LLMs) continue to advance, they are increasingly relied upon as real-time sources of information by non-expert users. To ensure the factuality of the info…