April 3, 2024, 4:47 a.m. | Chaitanya Malaviya, Subin Lee, Sihao Chen, Elizabeth Sieber, Mark Yatskar, Dan Roth

cs.CL updates on arXiv.org arxiv.org

arXiv:2309.07852v2 Announce Type: replace
Abstract: As language models are adopted by a more sophisticated and diverse set of users, the importance of guaranteeing that they provide factually correct information supported by verifiable sources is critical across fields of study. This is especially the case for high-stakes fields, such as medicine and law, where the risk of propagating false information is high and can lead to undesirable societal consequences. Previous work studying attribution and factuality has not focused on analyzing these …

abstract arxiv case cs.ai cs.cl diverse expert fields importance information language language models law medicine questions set study type

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