Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Nadav Oved"'
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 11, Pp 351-366 (2023)
AbstractMost work on modeling the conversation history in Conversational Question Answering (CQA) reports a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether th
Externí odkaz:
https://doaj.org/article/726b0fbd48a4409c8db18ebe71a289d9
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 10, Pp 414-433 (2022)
AbstractNatural Language Processing algorithms have made incredible progress, but they still struggle when applied to out-of-distribution examples. We address a challenging and underexplored version of this domain adaptation problem, where an algorit
Externí odkaz:
https://doaj.org/article/70df35bbb2a14d478da32b49f3c4cc9c
Publikováno v:
Computational Linguistics, Vol 47, Iss 2, Pp 333-386 (2021)
AbstractUnderstanding predictions made by deep neural networks is notoriously difficult, but also crucial to their dissemination. As all machine learning–based methods, they are as good as their training data, and can also capture unwanted biases.
Externí odkaz:
https://doaj.org/article/695c189dcd6c464bb43626363309264e
Publikováno v:
Computational Linguistics, Vol 46, Iss 3 (2020)
Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. Although there is an abundance of computational work on player metrics prediction based on past performance, v
Externí odkaz:
https://doaj.org/article/66b43b8683cc48249e038c9c29c54721
Publikováno v:
Computational Linguistics. 46:667-712
Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. While there is an abundance of computational work on player metrics prediction based on past performance, very
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a3d59652dc8a68a5a38c109429a27377
https://doi.org/10.1162/coli_a_00383
https://doi.org/10.1162/coli_a_00383
Most works on modeling the conversation history in Conversational Question Answering (CQA) report a single main result on a common CQA benchmark. While existing models show impressive results on CQA leaderboards, it remains unclear whether they are r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a5dafc2e25effc952018021020d6e67
Autor:
Ran Levy, Nadav Oved
Publikováno v:
ACL/IJCNLP (1)
The product reviews summarization task aims to automatically produce a short summary for a set of reviews of a given product. Such summaries are expected to aggregate a range of different opinions in a concise, coherent and informative manner. This c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60e793a5875b26c3a5920d753a8265f5
https://doi.org/10.18653/v1/2021.acl-long.30
https://doi.org/10.18653/v1/2021.acl-long.30
Understanding predictions made by deep neural networks is notoriously difficult, but also crucial to their dissemination. As all machine learning based methods, they are as good as their training data, and can also capture unwanted biases. While ther
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f170c02af360cd7783d500844778fd63
http://arxiv.org/abs/2005.13407
http://arxiv.org/abs/2005.13407