Zobrazeno 1 - 10 of 93 pro vyhledávání: '"Sewon Min"'
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Akademický článek
InSCIt: Information-Seeking Conversations with Mixed-Initiative Interactions
Autor: Zeqiu Wu, Ryu Parish, Hao Cheng, Sewon Min, Prithviraj Ammanabrolu, Mari Ostendorf, Hannaneh Hajishirzi
Publikováno v: Transactions of the Association for Computational Linguistics, Vol 11, Pp 453-468 (2023)
AbstractIn an information-seeking conversation, a user may ask questions that are under-specified or unanswerable. An ideal agent would interact by initiating different response types according to the available knowledge sources. However, most curren
Externí odkaz: https://doaj.org/article/ece55ee3d6294fe3b867f5436a755131
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2
InSCIt: Information-Seeking Conversations with Mixed-Initiative Interactions
Autor: Zeqiu Wu, Ryu Parish, Hao Cheng, Sewon Min, Prithviraj Ammanabrolu, Mari Ostendorf, Hannaneh Hajishirzi
Publikováno v: Transactions of the Association for Computational Linguistics. 11:453-468
In an information-seeking conversation, a user may ask questions that are under-specified or unanswerable. An ideal agent would interact by initiating different response types according to the available knowledge sources. However, most current studie
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a0d1729a0a6f37c7f4b0a18608129e81
https://doi.org/10.1162/tacl_a_00559
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10
MetaICL: Learning to Learn In Context
Autor: Sewon Min, Mike Lewis, Luke Zettlemoyer, Hannaneh Hajishirzi
We introduce MetaICL (Meta-training for In-Context Learning), a new meta-training framework for few-shot learning where a pretrained language model is tuned to do in-context learning on a large set of training tasks. This meta-training enables the mo
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ed567a0ccf0c8d33fe2d7094a2e1c7b
http://arxiv.org/abs/2110.15943
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