Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Niki Parmar"'
Dense retrieval has been shown to be effective for retrieving relevant documents for Open Domain QA, surpassing popular sparse retrieval methods like BM25. REALM (Guu et al., 2020) is an end-to-end dense retrieval system that relies on MLM based pret
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b3703fe1e5b35f192f67b33846bf482
http://arxiv.org/abs/2104.08710
http://arxiv.org/abs/2104.08710
Autor:
Jonathon Shlens, Blake A. Hechtman, Aravind Srinivas, Ashish Vaswani, Niki Parmar, Prajit Ramachandran
Publikováno v:
CVPR
Self-attention has the promise of improving computer vision systems due to parameter-independent scaling of receptive fields and content-dependent interactions, in contrast to parameter-dependent scaling and content-independent interactions of convol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2391247bd9fbaf3096c36d9e4458e10
http://arxiv.org/abs/2103.12731
http://arxiv.org/abs/2103.12731
Publikováno v:
CVPR
We present BoTNet, a conceptually simple yet powerful backbone architecture that incorporates self-attention for multiple computer vision tasks including image classification, object detection and instance segmentation. By just replacing the spatial
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e556aa4923add858e5fc6a8ee8c189d4
Autor:
Niki Parmar, James Qin, Ruoming Pang, Zhengdong Zhang, Yu Zhang, Chung-Cheng Chiu, Anmol Gulati, Yonghui Wu, Jiahui Yu, Shibo Wang, Wei Han
Publikováno v:
INTERSPEECH
Recently Transformer and Convolution neural network (CNN) based models have shown promising results in Automatic Speech Recognition (ASR), outperforming Recurrent neural networks (RNNs). Transformer models are good at capturing content-based global i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5e747a2aca22bd59991b14ed380e109
Publikováno v:
NAACL-HLT (1)
Grammatical Error Correction (GEC) has been recently modeled using the sequence-to-sequence framework. However, unlike sequence transduction problems such as machine translation, GEC suffers from the lack of plentiful parallel data. We describe two a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10feab180b6b16069a680b6528219347
https://doi.org/10.18653/v1/n19-1333
https://doi.org/10.18653/v1/n19-1333
Autor:
Ashish Vaswani, Zhifeng Chen, Mia Xu Chen, Noam Shazeer, Llion Jones, Jakob Uszkoreit, Ankur Bapna, Mike Schuster, Macduff Hughes, Yonghui Wu, George Foster, Melvin Johnson, Niki Parmar, Lukasz Kaiser, Orhan Firat, Wolfgang Macherey
Publikováno v:
ACL (1)
The past year has witnessed rapid advances in sequence-to-sequence (seq2seq) modeling for Machine Translation (MT). The classic RNN-based approaches to MT were first out-performed by the convolutional seq2seq model, which was then out-performed by th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f69bd3bf711cd446072c004b5c6789f
https://doi.org/10.18653/v1/p18-1008
https://doi.org/10.18653/v1/p18-1008
Autor:
Jesse Graham, Stephen Vaisey, Kate M. Johnson, Rumen Iliev, Niki Parmar, Joe Hoover, Morteza Dehghani, Justin Garten, Eyal Sagi
Publikováno v:
Journal of experimental psychology. General. 145(3)
Does sharing moral values encourage people to connect and form communities? The importance of moral homophily (love of same) has been recognized by social scientists, but the types of moral similarities that drive this phenomenon are still unknown. U
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e5664bf5ea8ee988be3575b426f5c01
https://pubmed.ncbi.nlm.nih.gov/26726910
https://pubmed.ncbi.nlm.nih.gov/26726910
Autor:
Justin Garten, Vijayan Balasubramanian, Yuvarani Shankar, Aswin Rajkumar, Anurag Singh, Linda Pulickal, Morteza Dehghani, Reihane Boghrati, Kate M. Johnson, Joe Hoover, Niki Parmar
Publikováno v:
SSRN Electronic Journal.
As human activity and interaction increasingly take place online, the digital residues of these activities provide a valuable window into a range of psychological and social processes. A great deal of progress has been made toward utilizing these opp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c353f5089f4ba0af112ff3239df846f6
https://doi.org/10.2139/ssrn.2660651
https://doi.org/10.2139/ssrn.2660651