Web: http://arxiv.org/abs/2201.06796

Jan. 26, 2022, 2:10 a.m. | Mina Lee, Percy Liang, Qian Yang

cs.CL updates on arXiv.org arxiv.org

Large language models (LMs) offer unprecedented language generation
capabilities and exciting opportunities for interaction design. However, their
highly context-dependent capabilities are difficult to grasp and are often
subjectively interpreted. In this paper, we argue that by curating and
analyzing large interaction datasets, the HCI community can foster more
incisive examinations of LMs' generative capabilities. Exemplifying this
approach, we present CoAuthor, a dataset designed for revealing GPT-3's
capabilities in assisting creative and argumentative writing. CoAuthor captures
rich interactions between 63 writers …

ai arxiv collaborative dataset human language language model model writing

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