Teaching LLMs to Abstain across Languages via Multilingual Feedback
Multilingual feedback teaches LLMs to abstain from answering in low-resource languages and improves cross-lingual abstention without degrading performance.
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Multilingual feedback advances cross-language abstention coverage with a clean split, though it remains essentially self-correction repackaged and unproven for low-resource refusal beyond translated patterns.
Abstract
Shangbin Feng, Weijia Shi, Yike Wang, Wenxuan Ding, Orevaoghene Ahia, Shuyue Stella Li, Vidhisha Balachandran, Sunayana Sitaram, Yulia Tsvetkov. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 2024.