Zobrazeno 1 - 10
of 131
pro vyhledávání: '"James, Rich"'
Autor:
Shi, Weijia, Min, Sewon, Lomeli, Maria, Zhou, Chunting, Li, Margaret, Szilvasy, Gergely, James, Rich, Lin, Xi Victoria, Smith, Noah A., Zettlemoyer, Luke, Yih, Scott, Lewis, Mike
Large language models (LMs) are currently trained to predict tokens given document prefixes, enabling them to directly perform long-form generation and prompting-style tasks which can be reduced to document completion. Existing pretraining pipelines
Externí odkaz:
http://arxiv.org/abs/2310.10638
Autor:
Lin, Xi Victoria, Chen, Xilun, Chen, Mingda, Shi, Weijia, Lomeli, Maria, James, Rich, Rodriguez, Pedro, Kahn, Jacob, Szilvasy, Gergely, Lewis, Mike, Zettlemoyer, Luke, Yih, Scott
Retrieval-augmented language models (RALMs) improve performance by accessing long-tail and up-to-date knowledge from external data stores, but are challenging to build. Existing approaches require either expensive retrieval-specific modifications to
Externí odkaz:
http://arxiv.org/abs/2310.01352
Autor:
Shi, Weijia, Min, Sewon, Yasunaga, Michihiro, Seo, Minjoon, James, Rich, Lewis, Mike, Zettlemoyer, Luke, Yih, Wen-tau
We introduce REPLUG, a retrieval-augmented language modeling framework that treats the language model (LM) as a black box and augments it with a tuneable retrieval model. Unlike prior retrieval-augmented LMs that train language models with special cr
Externí odkaz:
http://arxiv.org/abs/2301.12652
Autor:
William Jin, Christopher Montoya, Benjamin James Rich, Crystal Seldon Taswell, Miguel Noy, Deukwoo Kwon, Benjamin Spieler, Brandon Mahal, Matthew Abramowitz, Raphael Yechieli, Alan Pollack, Alan Dal Pra
Publikováno v:
JMIR Cancer, Vol 10, p e51061 (2024)
BackgroundPatients with prostate cancer undergoing radiation therapy (RT) need comfortably full bladders to reduce toxicities during treatment. Poor compliance is common with standard of care written or verbal instructions, leading to wasted patient
Externí odkaz:
https://doaj.org/article/f18c54503e7c411aa18777d06e145207
Autor:
Yasunaga, Michihiro, Aghajanyan, Armen, Shi, Weijia, James, Rich, Leskovec, Jure, Liang, Percy, Lewis, Mike, Zettlemoyer, Luke, Yih, Wen-tau
Recent multimodal models such as DALL-E and CM3 have achieved remarkable progress in text-to-image and image-to-text generation. However, these models store all learned knowledge (e.g., the appearance of the Eiffel Tower) in the model parameters, req
Externí odkaz:
http://arxiv.org/abs/2211.12561
Autor:
Tatiana Shaurova, Lingyue Yan, Yafei Su, Laurie James Rich, Vui King Vincent‐Chong, Hannah Calkins, Saraswati Pokharel, Martin Petkovich, Mukund Seshadri, Yun Wu, Pamela Anne Hershberger
Publikováno v:
Cancer Communications, Vol 43, Iss 4, Pp 503-507 (2023)
Externí odkaz:
https://doaj.org/article/4c6eb2db26ac4ab8ba970459644a9b28
Publikováno v:
Review of Accounting and Finance. 21:299-319
Purpose This paper aims to examine the impact on firm financial distress by industry of one of the most recent accounting changes in the treatment of operating leases, Financial Accounting Standard Board (FASB) Accounting Standards Update (ASU) No. 2
Autor:
Seshadri Nadathur, Alex Woodfinden, Will J Percival, Marie Aubert, Julian Bautista, Kyle Dawson, Stéphanie Escoffier, Sebastien Fromenteau, Héctor Gil-Marín, James Rich, Ashley J Ross, Graziano Rossi, Mariana Vargas Magaña, Joel R Brownstein, Donald P Schneider
Publikováno v:
Monthly Notices of the Royal Astronomical Society. 516:2936-2937
Autor:
Samantha Youles, Julian E Bautista, Andreu Font-Ribera, David Bacon, James Rich, David Brooks, Tamara M Davis, Kyle Dawson, Axel de la Macorra, Govinda Dhungana, Peter Doel, Kevin Fanning, Enrique Gaztañaga, Satya Gontcho A Gontcho, Alma X Gonzalez-Morales, Julien Guy, Klaus Honscheid, Vid Iršič, Robert Kehoe, David Kirkby, Theodore Kisner, Martin Landriau, Laurent Le Guillou, Michael E Levi, Paul Martini, Andrea Muñoz-Gutiérrez, Nathalie Palanque-Delabrouille, Ignasi Pérez-Ràfols, Claire Poppett, César Ramírez-Pérez, Michael Schubnell, Gregory Tarlé, Michael Walther
Publikováno v:
Mon.Not.Roy.Astron.Soc.
Mon.Not.Roy.Astron.Soc., 2022, 516 (1), pp.421-433. ⟨10.1093/mnras/stac2102⟩
Mon.Not.Roy.Astron.Soc., 2022, 516 (1), pp.421-433. ⟨10.1093/mnras/stac2102⟩
Using synthetic Lyman-$\alpha$ forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-$\alpha$ correlation functions. Estimates of quasar redsh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d25579465973f315f3d03c4e6a20d068
http://arxiv.org/abs/2205.06648
http://arxiv.org/abs/2205.06648