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pro vyhledávání: '"Hsu I"'
Autor:
Hsu, I-Hung, Wang, Zifeng, Le, Long T., Miculicich, Lesly, Peng, Nanyun, Lee, Chen-Yu, Pfister, Tomas
Grounded generation aims to equip language models (LMs) with the ability to produce more credible and accountable responses by accurately citing verifiable sources. However, existing methods, by either feeding LMs with raw or preprocessed materials,
Externí odkaz:
http://arxiv.org/abs/2406.05365
Autor:
Hsu, I-Hung, Xue, Zihan, Pochh, Nilay, Bansal, Sahil, Natarajan, Premkumar, Srinivasa, Jayanth, Peng, Nanyun
Event linking connects event mentions in text with relevant nodes in a knowledge base (KB). Prior research in event linking has mainly borrowed methods from entity linking, overlooking the distinct features of events. Compared to the extensively expl
Externí odkaz:
http://arxiv.org/abs/2403.15097
Autor:
Huang, Kuan-Hao, Hsu, I-Hung, Parekh, Tanmay, Xie, Zhiyu, Zhang, Zixuan, Natarajan, Premkumar, Chang, Kai-Wei, Peng, Nanyun, Ji, Heng
Event extraction has gained considerable interest due to its wide-ranging applications. However, recent studies draw attention to evaluation issues, suggesting that reported scores may not accurately reflect the true performance. In this work, we ide
Externí odkaz:
http://arxiv.org/abs/2311.09562
Label projection, which involves obtaining translated labels and texts jointly, is essential for leveraging machine translation to facilitate cross-lingual transfer in structured prediction tasks. Prior research exploring label projection often compr
Externí odkaz:
http://arxiv.org/abs/2309.08943
Event argument extraction (EAE) identifies event arguments and their specific roles for a given event. Recent advancement in generation-based EAE models has shown great performance and generalizability over classification-based models. However, exist
Externí odkaz:
http://arxiv.org/abs/2305.16734
Existing efforts on text synthesis for code-switching mostly require training on code-switched texts in the target language pairs, limiting the deployment of the models to cases lacking code-switched data. In this work, we study the problem of synthe
Externí odkaz:
http://arxiv.org/abs/2305.16724
Paraphrase generation is a long-standing task in natural language processing (NLP). Supervised paraphrase generation models, which rely on human-annotated paraphrase pairs, are cost-inefficient and hard to scale up. On the other hand, automatically a
Externí odkaz:
http://arxiv.org/abs/2305.16585
Relation Extraction (RE) has been extended to cross-document scenarios because many relations are not simply described in a single document. This inevitably brings the challenge of efficient open-space evidence retrieval to support the inference of c
Externí odkaz:
http://arxiv.org/abs/2212.10786
Autor:
HSU，I-HSUAN, 許以暄
107
This paper is designed as a written dissertation, based on the creation works from 2016 to 2019, which are taken as the study subjects. Its contents include the literature exploration of academic theories and individual creation context. In
This paper is designed as a written dissertation, based on the creation works from 2016 to 2019, which are taken as the study subjects. Its contents include the literature exploration of academic theories and individual creation context. In
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/kzkgeh
Autor:
Hsu, I-Ying, Tsai, Fu-Hsing
Publikováno v:
Educational Technology & Society, 2023 Oct 01. 26(4), 38-50.
Externí odkaz:
https://www.jstor.org/stable/48747519
