Zobrazeno 1 - 10
of 731
pro vyhledávání: '"Shamis, P."'
Autor:
Yasunaga, Michihiro, Shamis, Leonid, Zhou, Chunting, Cohen, Andrew, Weston, Jason, Zettlemoyer, Luke, Ghazvininejad, Marjan
Recent approaches to large language model (LLM) alignment typically require millions of human annotations or rely on external aligned models for synthetic data generation. This paper introduces ALMA: Alignment with Minimal Annotation, demonstrating t
Externí odkaz:
http://arxiv.org/abs/2412.04305
Autor:
Fernandez, Jared, Wehrstedt, Luca, Shamis, Leonid, Elhoushi, Mostafa, Saladi, Kalyan, Bisk, Yonatan, Strubell, Emma, Kahn, Jacob
Dramatic increases in the capabilities of neural network models in recent years are driven by scaling model size, training data, and corresponding computational resources. To develop the exceedingly large networks required in modern applications, suc
Externí odkaz:
http://arxiv.org/abs/2411.13055
Autor:
Sawani, Youssef Mohammad
Publikováno v:
African Studies Review (Project Muse); September 2024, Vol. 67 Issue: 1 p240-242, 3p
Autor:
Lee, Yejin, Sun, Anna, Hosmer, Basil, Acun, Bilge, Balioglu, Can, Wang, Changhan, Hernandez, Charles David, Puhrsch, Christian, Haziza, Daniel, Guessous, Driss, Massa, Francisco, Kahn, Jacob, Wan, Jeffrey, Reizenstein, Jeremy, Zhai, Jiaqi, Isaacson, Joe, Schlosser, Joel, Pino, Juan, Sadagopan, Kaushik Ram, Shamis, Leonid, Ma, Linjian, Hwang, Min-Jae, Chen, Mingda, Elhoushi, Mostafa, Rodriguez, Pedro, Pasunuru, Ram, Yih, Scott, Popuri, Sravya, Liu, Xing, Wu, Carole-Jean
Generative artificial intelligence (AI) technology is revolutionizing the computing industry. Not only its applications have broadened to various sectors but also poses new system design and optimization opportunities. The technology is capable of un
Externí odkaz:
http://arxiv.org/abs/2410.00215
Autor:
Zhou, Chunting, Yu, Lili, Babu, Arun, Tirumala, Kushal, Yasunaga, Michihiro, Shamis, Leonid, Kahn, Jacob, Ma, Xuezhe, Zettlemoyer, Luke, Levy, Omer
We introduce Transfusion, a recipe for training a multi-modal model over discrete and continuous data. Transfusion combines the language modeling loss function (next token prediction) with diffusion to train a single transformer over mixed-modality s
Externí odkaz:
http://arxiv.org/abs/2408.11039
Autor:
Nvidia, Adler, Bo, Agarwal, Niket, Aithal, Ashwath, Anh, Dong H., Bhattacharya, Pallab, Brundyn, Annika, Casper, Jared, Catanzaro, Bryan, Clay, Sharon, Cohen, Jonathan, Das, Sirshak, Dattagupta, Ayush, Delalleau, Olivier, Derczynski, Leon, Dong, Yi, Egert, Daniel, Evans, Ellie, Ficek, Aleksander, Fridman, Denys, Ghosh, Shaona, Ginsburg, Boris, Gitman, Igor, Grzegorzek, Tomasz, Hero, Robert, Huang, Jining, Jawa, Vibhu, Jennings, Joseph, Jhunjhunwala, Aastha, Kamalu, John, Khan, Sadaf, Kuchaiev, Oleksii, LeGresley, Patrick, Li, Hui, Liu, Jiwei, Liu, Zihan, Long, Eileen, Mahabaleshwarkar, Ameya Sunil, Majumdar, Somshubra, Maki, James, Martinez, Miguel, de Melo, Maer Rodrigues, Moshkov, Ivan, Narayanan, Deepak, Narenthiran, Sean, Navarro, Jesus, Nguyen, Phong, Nitski, Osvald, Noroozi, Vahid, Nutheti, Guruprasad, Parisien, Christopher, Parmar, Jupinder, Patwary, Mostofa, Pawelec, Krzysztof, Ping, Wei, Prabhumoye, Shrimai, Roy, Rajarshi, Saar, Trisha, Sabavat, Vasanth Rao Naik, Satheesh, Sanjeev, Scowcroft, Jane Polak, Sewall, Jason, Shamis, Pavel, Shen, Gerald, Shoeybi, Mohammad, Sizer, Dave, Smelyanskiy, Misha, Soares, Felipe, Sreedhar, Makesh Narsimhan, Su, Dan, Subramanian, Sandeep, Sun, Shengyang, Toshniwal, Shubham, Wang, Hao, Wang, Zhilin, You, Jiaxuan, Zeng, Jiaqi, Zhang, Jimmy, Zhang, Jing, Zhang, Vivienne, Zhang, Yian, Zhu, Chen
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distri
Externí odkaz:
http://arxiv.org/abs/2406.11704
Autor:
Fallon, Peter K.
Publikováno v:
Explorations in Media Ecology; June 2023, Vol. 22 Issue: 2 p247-253, 7p
Autor:
Suad A. K. Shamis, Jean Quinn, Sara Al‐Badran, Molly McKenzie, Phimmada Hatthakarnkul, Gerard Lynch, Guang‐Yu Lian, Warapan Numprasit, Laszlo Romics Jr., Ditte Andersen, Elizabeth Mallon, Donald C. McMillan, Joanne Edwards
Publikováno v:
Cancer Medicine, Vol 13, Iss 23, Pp n/a-n/a (2024)
ABSTRACT Purpose Carbonic anhydrase IX (CAIX) is a well‐established prognostic marker in breast cancer (BC). Nevertheless, this prognostic value is yet to be confirmed in BC subtypes. This study aims to investigate the prognostic effects of CAIX in
Externí odkaz:
https://doaj.org/article/ad007217817e49efbb9a5189043e7aab
In this paper, we present a framework for moving compute and data between processing elements in a distributed heterogeneous system. The implementation of the framework is based on the LLVM compiler toolchain combined with the UCX communication frame
Externí odkaz:
http://arxiv.org/abs/2208.01154
Marketplaces for machine learning (ML) models are emerging as a way for organizations to monetize models. They allow model owners to retain control over hosted models by using cloud resources to execute ML inference requests for a fee, preserving mod
Externí odkaz:
http://arxiv.org/abs/2205.15757