Zobrazeno 1 - 10
of 19
pro vyhledávání: '"S H Lewis"'
Autor:
Patrick S. H. Lewis, Sebastian Riedel, Linqing Liu, Yuxiang Wu, Heinrich Küttler, Pasquale Minervini, Aleksandra Piktus, Pontus Stenetorp
Publikováno v:
Transactions of the Association for Computational Linguistics. 9:1098-1115
Open-domain Question Answering models that directly leverage question-answer (QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in terms of speed and memory compared with conventional models which retrieve and read
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99130aa9bdb6bbd27da823217c2d8086
https://doi.org/10.1162/tacl_a_00415
https://doi.org/10.1162/tacl_a_00415
Publikováno v:
EACL
Ideally Open-Domain Question Answering models should exhibit a number of competencies, ranging from simply memorizing questions seen at training time, to answering novel question formulations with answers seen during training, to generalizing to comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8dcfc175a15ac86602a90a9d4acc747b
Autor:
Sergey Edunov, Wen-tau Yih, Danqi Chen, Vladimir Karpukhin, Sewon Min, Barlas Oguz, Patrick S. H. Lewis, Ledell Wu
Publikováno v:
EMNLP (1)
Open-domain question answering relies on efficient passage retrieval to select candidate contexts, where traditional sparse vector space models, such as TF-IDF or BM25, are the de facto method. In this work, we show that retrieval can be practically
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4586e4a9f0e9488de8d1bb2d039be7a3
Autor:
Patrick S. H. Lewis, Nicola De Cao, Aleksandra Piktus, Yacine Jernite, Jean Maillard, Angela Fan, James Thorne, Vassilis Plachouras, Vladimir Karpukhin, Tim Rocktäschel, Sebastian Riedel, Majid Yazdani, Fabio Petroni
Publikováno v:
NAACL-HLT
Challenging problems such as open-domain question answering, fact checking, slot filling and entity linking require access to large, external knowledge sources. While some models do well on individual tasks, developing general models is difficult as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::858c48f1c93a18c525f01a73ceda1250
Publikováno v:
EMNLP (1)
We aim to improve question answering (QA) by decomposing hard questions into simpler sub-questions that existing QA systems are capable of answering. Since labeling questions with decompositions is cumbersome, we take an unsupervised approach to prod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::37accd8288bed9628091f30f7e493786
Publikováno v:
ClinicalNLP@EMNLP
A large array of pretrained models are available to the biomedical NLP (BioNLP) community. Finding the best model for a particular task can be difficult and time-consuming. For many applications in the biomedical and clinical domains, it is crucial t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::213ee3584b01e8b1f556b5f96cfe2ae7
https://doi.org/10.18653/v1/2020.clinicalnlp-1.17
https://doi.org/10.18653/v1/2020.clinicalnlp-1.17
Publikováno v:
ACL (1)
Obtaining training data for Question Answering (QA) is time-consuming and resource-intensive, and existing QA datasets are only available for limited domains and languages. In this work, we explore to what extent high quality training data is actuall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::586b2732f929e08d599ec2162427134f
http://arxiv.org/abs/1906.04980
http://arxiv.org/abs/1906.04980
Autor:
Tim Rocktäschel, Sebastian Riedel, Patrick S. H. Lewis, Yuxiang Wu, Anton Bakhtin, Fabio Petroni, Alexander H. Miller
Publikováno v:
EMNLP/IJCNLP (1)
Scopus-Elsevier
Scopus-Elsevier
Recent progress in pretraining language models on large textual corpora led to a surge of improvements for downstream NLP tasks. Whilst learning linguistic knowledge, these models may also be storing relational knowledge present in the training data,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa610bed0ce94658e3700a5ec78cad50
https://doi.org/10.18653/v1/d19-1250
https://doi.org/10.18653/v1/d19-1250
Autor:
Guillaume Bouchard, Marzieh Saeidi, Patrick S. H. Lewis, Michael Sheldon, Sebastian Riedel, Tim Rocktäschel, Max Bartolo, Sameer Singh
Publikováno v:
EMNLP
Most work in machine reading focuses on question answering problems where the answer is directly expressed in the text to read. However, many real-world question answering problems require the reading of text not because it contains the literal answe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::abe2f8cf6e61084635141d5359858af8
Autor:
S H, Lewis, E, Gilbert-Barness
Publikováno v:
Advances in pediatrics. 45
The placenta should not be overlooked as a source of much valuable diagnostic information. Close evaluation of the placenta and its attached membranes may reveal further information. Essential data may be obtained from pathologic examination, and if
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::2cf4b55bbdf1fc3b28555412b9ed37d9
https://pubmed.ncbi.nlm.nih.gov/9742304
https://pubmed.ncbi.nlm.nih.gov/9742304