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Long-form evaluation of model editing
Feb. 15, 2024, 5:46 a.m. | Domenic Rosati, Robie Gonzales, Jinkun Chen, Xuemin Yu, Melis Erkan, Yahya Kayani, Satya Deepika Chavatapalli, Frank Rudzicz, Hassan Sajjad
cs.CL updates on arXiv.org arxiv.org
Abstract: Evaluations of model editing currently only use the `next few token' completions after a prompt. As a result, the impact of these methods on longer natural language generation is largely unknown. We introduce long-form evaluation of model editing (\textbf{\textit{LEME}}) a novel evaluation protocol that measures the efficacy and impact of model editing in long-form generative settings. Our protocol consists of a machine-rated survey and a classifier which correlates well with human ratings. Importantly, we find …
abstract arxiv cs.cl editing evaluation form impact language language generation natural natural language natural language generation next novel prompt protocol token type
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