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Generate rather than Retrieve: Large Language Models are Strong Context Generators. (arXiv:2209.10063v2 [cs.CL] UPDATED)
Sept. 30, 2022, 1:17 a.m. | Wenhao Yu, Dan Iter, Shuohang Wang, Yichong Xu, Mingxuan Ju, Soumya Sanyal, Chenguang Zhu, Michael Zeng, Meng Jiang
cs.CL updates on arXiv.org arxiv.org
Knowledge-intensive tasks, such as open-domain question answering (QA),
require access to a large amount of world or domain knowledge. A common
approach for knowledge-intensive tasks is to employ a retrieve-then-read
pipeline that first retrieves a handful of relevant contextual documents from
an external corpus such as Wikipedia and then predicts an answer conditioned on
the retrieved documents. In this paper, we present a novel perspective for
solving knowledge-intensive tasks by replacing document retrievers with large
language model generators. We call …
arxiv context language language models large language models
More from arxiv.org / cs.CL updates on arXiv.org
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