Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Leon Weber"'
Autor:
Hugo Laurençon, Lucile Saulnier, Thomas Wang, Christopher Akiki, Albert Villanova del Moral, Teven Le Scao, Leandro von Werra, Chenghao Mou, Eduardo González Ponferrada, Huu Nguyen, Jörg Frohberg, Mario Šaško, Quentin Lhoest, Angelina Mcmillan-Major, Gérard Dupont, Stella Biderman, Anna Rogers, Loubna Ben Allal, Francesco de Toni, Giada Pistilli, Olivier Nguyen, Somaieh Nikpoor, Maraim Masoud, Pierre Colombo, Javier de la Rosa, Paulo Villegas, Tristan Thrush, Shayne Longpre, Sebastian Nagel, Leon Weber, Manuel Romero Muñoz, Jian Zhu, Daniel van Strien, Zaid Alyafeai, Khalid Almubarak, Vu Minh Chien, Itziar Gonzalez-Dios, Aitor Soroa, Kyle Lo, Manan Dey, Pedro Ortiz Suarez, Aaron Gokaslan, Shamik Bose, David Ifeoluwa Adelani, Long Phan, Hieu Tran, Ian Yu, Suhas Pai, Jenny Chim, Violette Lepercq, Suzana Ilić, Margaret Mitchell, Sasha Luccioni, Yacine Jernite
Publikováno v:
HAL
As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiative, was formed w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de4f6aa98013be0d5a61119e2bb20f3a
Publikováno v:
Database : the journal of biological databases and curation. 2022
The identification of chemical–protein interactions described in the literature is an important task with applications in drug design, precision medicine and biotechnology. Manual extraction of such relationships from the biomedical literature is c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f9af65fc6986f644309619f6a9a54e37
https://pubmed.ncbi.nlm.nih.gov/36399413
https://pubmed.ncbi.nlm.nih.gov/36399413
Autor:
Jason Fries, Natasha Seelam, Gabriel Altay, Leon Weber, Myungsun Kang, Debajyoti Datta, Ruisi Su, Samuele Garda, Bo Wang, Simon Ott, Matthias Samwald, Wojciech Kusa
Large-scale language modeling and natural language prompting have demonstrated exciting capabilities for few and zero shot learning in NLP. However, translating these successes to specialized domains such as biomedicine remains challenging, due in pa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a27c1a046aa3fb38a2437c1ed6ce82d2
http://edoc.mdc-berlin.de/22134/1/22134oa.pdf
http://edoc.mdc-berlin.de/22134/1/22134oa.pdf
Publikováno v:
Journal of Chemical Theory and Computation
Machine learning (ML) approaches have demonstrated the ability to predict molecular spectra at a fraction of the computational cost of traditional theoretical chemistry methods while maintaining high accuracy. Graph neural networks (GNNs) are particu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63893965d2e99c14fbf27b9b90963476
http://www.helmholtz-berlin.de/pubbin/oai_publication?VT=1&ID=108468
http://www.helmholtz-berlin.de/pubbin/oai_publication?VT=1&ID=108468
Publikováno v:
Proceedings of the 21st Workshop on Biomedical Language Processing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f9f65ad7973fc55d67dc5b730bf8e1a8
https://doi.org/10.18653/v1/2022.bionlp-1.28
https://doi.org/10.18653/v1/2022.bionlp-1.28
Publikováno v:
Proceedings
Deriving and modifying graphs from natural language text has become a versatile basis technology for information extraction with applications in many subfields, such as semantic parsing or knowledge graph construction. A recent work used this techniq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::05fb1c0116b00f7aa33971648cb23900
http://edoc.mdc-berlin.de/21568/1/21568oa.pdf
http://edoc.mdc-berlin.de/21568/1/21568oa.pdf
Publikováno v:
Bioinformatics
Summary: Named Entity Recognition (NER) is an important step in biomedical information extraction pipelines. Tools for NER should be easy to use, cover multiple entity types, highly accurate, and robust towards variations in text genre and style. To
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c89f7475140fdcbf7a7f8a6de4860ca9
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5005588_2/component/file_5008100/5005588.pdf
https://gfzpublic.gfz-potsdam.de/pubman/item/item_5005588_2/component/file_5008100/5005588.pdf
Publikováno v:
BioNLP@NAACL-HLT
This paper describes our contribution for the MEDIQA-2021 Task 1 question summarization competition. We model the task as conditional generation problem. Our concrete pipeline performs a finetuning of the large pretrained generative transformers PEGA
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ecc2cc24517a1fb7e08a38a61354597
https://doi.org/10.18653/v1/2021.bionlp-1.9
https://doi.org/10.18653/v1/2021.bionlp-1.9
Publikováno v:
Bioinformatics
Motivation A significant portion of molecular biology investigates signalling pathways and thus depends on an up-to-date and complete resource of functional protein–protein associations (PPAs) that constitute such pathways. Despite extensive curati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0203c6801414288a9cbbfd185afa94a
https://pubmed.ncbi.nlm.nih.gov/32657389
https://pubmed.ncbi.nlm.nih.gov/32657389
Publikováno v:
LOUHI@EMNLP
Biomedical event extraction from natural text is a challenging task as it searches for complex and often nested structures describing specific relationships between multiple molecular entities, such as genes, proteins, or cellular components. It usua
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eddf8b553a1fcbcfa612de26c1352db6
https://doi.org/10.18653/v1/2020.louhi-1.10
https://doi.org/10.18653/v1/2020.louhi-1.10