Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Dara Bahri"'
Publikováno v:
ACM SIGIR Forum. 55:1-27
When experiencing an information need, users want to engage with a domain expert, but often turn to an information retrieval system, such as a search engine, instead. Classical information retrieval systems do not answer information needs directly, b
Publikováno v:
WSDM
Large generative language models such as GPT-2 are well-known for their ability to generate text as well as their utility in supervised downstream tasks via fine-tuning. Its prevalence on the web, however, is still not well understood - if we run GPT
Publikováno v:
ACL/IJCNLP (1)
In the era of pre-trained language models, Transformers are the de facto choice of model architectures. While recent research has shown promise in entirely convolutional, or CNN, architectures, they have not been explored using the pre-train-fine-tun
Publikováno v:
ACL/IJCNLP (1)
There are two major classes of natural language grammar -- the dependency grammar that models one-to-one correspondences between words and the constituency grammar that models the assembly of one or several corresponded words. While previous unsuperv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ecd84c2d59a8f2537d939d118d3ebd4
http://arxiv.org/abs/2012.00857
http://arxiv.org/abs/2012.00857
Transformer model architectures have garnered immense interest lately due to their effectiveness across a range of domains like language, vision and reinforcement learning. In the field of natural language processing for example, Transformers have be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f6db57a3d0e1f1fccc07994657a8350e
http://arxiv.org/abs/2009.06732
http://arxiv.org/abs/2009.06732
Publikováno v:
SIGIR
Work in information retrieval has traditionally focused on ranking and relevance: given a query, return some number of results ordered by relevance to the user. However, the problem of determining how many results to return, i.e. how to optimally tru
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b539642c5faeb85397b4417d44bd871
Publikováno v:
ACL
This paper seeks to develop a deeper understanding of the fundamental properties of neural text generations models. The study of artifacts that emerge in machine generated text as a result of modeling choices is a nascent research area. Previously, t
Autor:
Ryan D. Sochol, Kosuke Iwai, L. Lo, Joanne Lo, Dara Bahri, Megan E. Dueck, Valerie S. Chang, Luke P. Lee, R. Ruelos, Liwei Lin
Publikováno v:
2011 IEEE 24th International Conference on Micro Electro Mechanical Systems.
Dynamic bead-based microarrays offer an ideal platform for chemical and biological applications, including on-site chemical analysis, point-of-care medical diagnostics and synthetic biology on a chip. Despite significant development of dynamic microa