Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Anton Bakhtin"'
Autor:
Anton, Bakhtin, Noam, Brown, Emily, Dinan, Gabriele, Farina, Colin, Flaherty, Daniel, Fried, Andrew, Goff, Jonathan, Gray, Hengyuan, Hu, Athul Paul, Jacob, Mojtaba, Komeili, Karthik, Konath, Minae, Kwon, Adam, Lerer, Mike, Lewis, Alexander H, Miller, Sasha, Mitts, Adithya, Renduchintala, Stephen, Roller, Dirk, Rowe, Weiyan, Shi, Joe, Spisak, Alexander, Wei, David, Wu, Hugh, Zhang, Markus, Zijlstra
Publikováno v:
Science (New York, N.Y.).
Despite much progress in training AI systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge. We introduce Cicero, the first AI agent to achie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::ee27674ce2ed5719073ce44a682f91d5
https://pubmed.ncbi.nlm.nih.gov/36413172
https://pubmed.ncbi.nlm.nih.gov/36413172
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
Publikováno v:
INTERSPEECH
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c9c635626962e195f340d03191ae94a
https://doi.org/10.21437/interspeech.2018-2061
https://doi.org/10.21437/interspeech.2018-2061
Publikováno v:
ASRU
We develop streaming keyword spotting systems using a recurrent neural network transducer (RNN-T) model: an all-neural, end-to-end trained, sequence-to-sequence model which jointly learns acoustic and language model components. Our models are trained
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20bbe599492b837daeab78c88d4b38e2
http://arxiv.org/abs/1710.09617
http://arxiv.org/abs/1710.09617
Publikováno v:
INTERSPEECH
In this paper we present a simple and computationally efficient quantization scheme that enables us to reduce the resolution of the parameters of a neural network from 32-bit floating point values to 8-bit integer values. The proposed quantization sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3014cad35417184e9ddd09a3ac6b07d3
Publikováno v:
CIKM
Query expansion for Information Retrieval is a challenging task. On the one hand, low quality expansion may hurt either recall, due to vocabulary mismatch, or precision, due to topic drift, and therefore reduce user satisfaction. On the other hand, u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::787f4df7eb6e1caa2114831d45e3c9ef
https://doi.org/10.1145/2505515.2507872
https://doi.org/10.1145/2505515.2507872