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Towards Safety and Helpfulness Balanced Responses via Controllable Large Language Models
April 2, 2024, 7:52 p.m. | Yi-Lin Tuan, Xilun Chen, Eric Michael Smith, Louis Martin, Soumya Batra, Asli Celikyilmaz, William Yang Wang, Daniel M. Bikel
cs.CL updates on arXiv.org arxiv.org
Abstract: As large language models (LLMs) become easily accessible nowadays, the trade-off between safety and helpfulness can significantly impact user experience. A model that prioritizes safety will cause users to feel less engaged and assisted while prioritizing helpfulness will potentially cause harm. Possible harms include teaching people how to build a bomb, exposing youth to inappropriate content, and hurting users' mental health. In this work, we propose to balance safety and helpfulness in diverse use cases …
abstract arxiv become cs.ai cs.cl experience harm impact language language models large language large language models llms responses safety trade trade-off type via will
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