Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Zeqiu Wu"'
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
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
Identifying relevant knowledge to be used in conversational systems that are grounded in long documents is critical to effective response generation. We introduce a knowledge identification model that leverages the document structure to provide dialo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fac1594fc1ee22f527618656fd44da9d
http://arxiv.org/abs/2109.04673
http://arxiv.org/abs/2109.04673
Publikováno v:
ACL/IJCNLP (Findings)
The advent of large pre-trained language models has made it possible to make high-quality predictions on how to add or change a sentence in a document. However, the high branching factor inherent to text generation impedes the ability of even the str
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e7e5daba6b23ae0083ace15bf724722
http://arxiv.org/abs/2106.07192
http://arxiv.org/abs/2106.07192
Publikováno v:
WSDM
Automatic relation extraction (RE) for types of interest is of great importance for interpreting massive text corpora in an efficient manner. Traditional RE models have heavily relied on human-annotated corpus for training, which can be costly in gen
Autor:
Zeqiu Wu
Publikováno v:
Mining Structures of Factual Knowledge from Text ISBN: 9783031007842
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ae078b15314630a7248b13bd19cbc3e
https://doi.org/10.1007/978-3-031-01912-8_10
https://doi.org/10.1007/978-3-031-01912-8_10
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783319712482
ECML/PKDD (1)
ECML/PKDD (1)
Corpus-based set expansion (i.e., finding the “complete” set of entities belonging to the same semantic class, based on a given corpus and a tiny set of seeds) is a critical task in knowledge discovery. It may facilitate numerous downstream appli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b881957f1f226f5892bdc6e5e82e6fe6
https://doi.org/10.1007/978-3-319-71249-9_18
https://doi.org/10.1007/978-3-319-71249-9_18
Autor:
Jiaming Shen, Jiawei Han, Fangbo Tao, Peipei Ping, David A. Liem, Xuan Wang, Richard M. Weinshilboum, Meng Jiang, Saurabh Sinha, Zeqiu Wu, Qi Zhu, Xiang Ren, Meng Qu
Publikováno v:
ACL (System Demonstrations)
Autor:
Zeqiu, Wu
Publikováno v:
Chinese Journal of Population Resources and Environment; January 2009, Vol. 7 Issue: 1 p82-88, 7p