Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Matt Gardner"'
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 9, Pp 195-210 (2021)
AbstractAnswering questions that involve multi-step reasoning requires decomposing them and using the answers of intermediate steps to reach the final answer. However, state-of-the-art models in grounded question answering often do not explicitly per
Externí odkaz:
https://doaj.org/article/70d8d63866354997b3ebe7146b9f6f54
Autor:
Allan S. Peake, Kerry L. Bell, R.A. Fischer, Matt Gardner, Bianca T. Das, Nick Poole, Michael Mumford
Publikováno v:
Frontiers in Plant Science, Vol 11 (2020)
Severe lodging of irrigated spring-wheat in sub-tropical Australia has previously caused yield loss of between 1.7 and 4.6 t ha–1 (20–60% of potential yield). In response, agronomic management options were assessed for their ability to reduce lod
Externí odkaz:
https://doaj.org/article/f752f2b7ef68491bac6cb6046c364c0e
Publikováno v:
ACM Computing Surveys. 55:1-45
Alongside huge volumes of research on deep learning models in NLP in the recent years, there has been also much work on benchmark datasets needed to track modeling progress. Question answering and reading comprehension have been particularly prolific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f073f7842d90e337edc195f72fcead9
https://doi.org/10.1145/3560260
https://doi.org/10.1145/3560260
Publikováno v:
Transactions of the Association for Computational Linguistics. 9:195-210
Answering questions that involve multi-step reasoning requires decomposing them and using the answers of intermediate steps to reach the final answer. However, state-of-the-art models in grounded question answering often do not explicitly perform dec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ddfa9942fbded60b6c4d28b5b3f5e9a
https://doi.org/10.1162/tacl_a_00361
https://doi.org/10.1162/tacl_a_00361
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98d50b2b7d1b3908abe1837315ed62c1
https://doi.org/10.18653/v1/2022.acl-long.195
https://doi.org/10.18653/v1/2022.acl-long.195
Controlled text perturbation is useful for evaluating and improving model generalizability. However, current techniques rely on training a model for every target perturbation, which is expensive and hard to generalize. We present Tailor, a semantical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad3d3b95e7ef2cefd7cfba72b80961df
http://arxiv.org/abs/2107.07150
http://arxiv.org/abs/2107.07150
Autor:
Matt Gardner
Publikováno v:
Journal of Commercial Biotechnology. 26
With the proliferation of types and business models in incubation and acceleration, a landscape survey commenced nearly a decade ago with innovation professionals running accelerators, incubators, corporate innovation teams, venture studios, and make
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b73c41abd9dfcace15b314312e1e469
https://doi.org/10.5912/jcb977
https://doi.org/10.5912/jcb977
Question Answering (QA) tasks requiring information from multiple documents often rely on a retrieval model to identify relevant information for reasoning. The retrieval model is typically trained to maximize the likelihood of the labeled supporting
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae3ab77c89ba469037e1209eafd86d53
Publikováno v:
ACL/IJCNLP (2)
The predominant challenge in weakly supervised semantic parsing is that of spurious programs that evaluate to correct answers for the wrong reasons. Prior work uses elaborate search strategies to mitigate the prevalence of spurious programs; however,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ac145a70e6dd8fbce31fbfe97c911f06
Autor:
Jesse Dodge, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell, Matt Gardner
Large language models have led to remarkable progress on many NLP tasks, and researchers are turning to ever-larger text corpora to train them. Some of the largest corpora available are made by scraping significant portions of the internet, and are f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa83ca31c7528aed69e4649c9fcfb530