3 papers
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…
cs.HC2025
Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
Mahjabin Nahar, Eun-Ju Lee, Jin Won Park +1
While we increasingly rely on large language models (LLMs) for various tasks, these models are known to produce inaccurate content or 'hallucinations' with potentially disastrous c…