Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Jason Weston"'
Publikováno v:
PLoS ONE, Vol 7, Iss 3, p e32235 (2012)
A variety of functionally important protein properties, such as secondary structure, transmembrane topology and solvent accessibility, can be encoded as a labeling of amino acids. Indeed, the prediction of such properties from the primary amino acid
Externí odkaz:
https://doaj.org/article/c4e9dbb680144721a426f3bf7a5128d3
Publikováno v:
PLoS Computational Biology, Vol 7, Iss 1, p e1001047 (2011)
Virtually every molecular biologist has searched a protein or DNA sequence database to find sequences that are evolutionarily related to a given query. Pairwise sequence comparison methods--i.e., measures of similarity between query and target sequen
Externí odkaz:
https://doaj.org/article/2a277e17bdbd4dd5add8156cd8a2073e
Publikováno v:
PLoS ONE, Vol 4, Iss 7, p e6393 (2009)
To reduce the increasing amount of time spent on literature search in the life sciences, several methods for automated knowledge extraction have been developed. Co-occurrence based approaches can deal with large text corpora like MEDLINE in an accept
Externí odkaz:
https://doaj.org/article/e00ebc70e9c548a597ec3f637edeff70
Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets.Pervasive and networked computers have dramatically red
Autor:
Jing Xu, Stephen Roller, Eric Michael Smith, Jason Weston, Yinhan Liu, Emily Dinan, Y-Lan Boureau, Mary Williamson, Naman Goyal, Myle Ott, Da Ju
Publikováno v:
EACL
Building open-domain chatbots is a challenging area for machine learning research. While prior work has shown that scaling neural models in the number of parameters and the size of the data they are trained on gives improved results, we highlight oth
Publikováno v:
NAACL-HLT
Conversational agents trained on large unlabeled corpora of human interactions will learn patterns and mimic behaviors therein, which include offensive or otherwise toxic behavior. We introduce a new human-and-model-in-the-loop framework for evaluati
Publikováno v:
ACL/IJCNLP (Findings)
Publikováno v:
ACL/IJCNLP (1)
To quantify how well natural language understanding models can capture consistency in a general conversation, we introduce the DialoguE COntradiction DEtection task (DECODE) and a new conversational dataset containing both human-human and human-bot c
Recent work in open-domain conversational agents has demonstrated that significant improvements in model engagingness and humanness metrics can be achieved via massive scaling in both pre-training data and model size (Adiwardana et al., 2020; Roller
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0cc1745cb99bc33eea51ade82c7e1c6d
http://arxiv.org/abs/2010.01082
http://arxiv.org/abs/2010.01082
Autor:
Margaret Li, Jack Urbanek, Jason Weston, Prithviraj Ammanabrolu, Tim Rocktäschel, Arthur Szlam
Publikováno v:
NAACL-HLT
We seek to create agents that both act and communicate with other agents in pursuit of a goal. Towards this end, we extend LIGHT (Urbanek et al. 2019) -- a large-scale crowd-sourced fantasy text-game -- with a dataset of quests. These contain natural
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf7c3080c4ac0fba0f16f35c88ca66f9
http://arxiv.org/abs/2010.00685
http://arxiv.org/abs/2010.00685