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cs.CL2025
LLM Knowledge is Brittle: Truthfulness Representations Rely on Superficial Resemblance
Patrick Haller, Mark Ibrahim, Polina Kirichenko +2
For Large Language Models (LLMs) to be reliable, they must learn robust knowledge that can be generally applied in diverse settings -- often unlike those seen during training. Yet,…
cs.CL2025
Translate, then Detect: Leveraging Machine Translation for Cross-Lingual Toxicity Classification
Samuel J. Bell, Eduardo Sánchez, David Dale +3
Multilingual toxicity detection remains a significant challenge due to the scarcity of training data and resources for many languages. While prior work has leveraged the translate-…