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cs.HC2026
When AI Says "I Am Unable to Answer": Understanding User Responses to AI Refusals
Mahjabin Nahar, Eun-Ju Lee, Yujin Heo +1
While refusal-based safeguards to mitigate hallucinations in large language models (LLMs) are becoming increasingly common, they may conflict with users' preferences for definitive…
cs.CL2026
TriBench-Ko: Evaluating LLM Risks in Judicial Workflows
Haesung Lee, Gyubin Choi, Eun-Ju Lee +5
Large language models (LLMs) are increasingly integrated into legal workflows. However, existing benchmarks primarily address proxy tasks, such as bar examination performance or cl…
cs.CV2026
Before Forgetting, Learn to Remember: Revisiting Foundational Learning Failures in LVLM Unlearning Benchmarks
JuneHyoung Kwon, MiHyeon Kim, Eunju Lee +3
While Large Vision-Language Models (LVLMs) offer powerful capabilities, they pose privacy risks by unintentionally memorizing sensitive personal information. Current unlearning ben…