Zobrazeno 1 - 10
of 21 866
pro vyhledávání: '"Egert A."'
Autor:
Egert, Moritz, Kosmala, Benjamin W.
Kalton and Mitrea characterized complex interpolation spaces of quasi-Banach function spaces as Calder\'on products if both interpolants are separable. We show that one separability assumption may be omitted and establish a Wolff-reiteration result w
Externí odkaz:
http://arxiv.org/abs/2412.12769
We study the operator \[ \partial_t - \text{div} A \nabla + B \cdot \nabla \] in parabolic upper-half-space, where $A$ is an elliptic matrix satisfying an oscillation condition and $B$ is a singular drift with a Carleson control. Our main result esta
Externí odkaz:
http://arxiv.org/abs/2412.09301
We present a data-driven analysis of dipole strength functions across the nuclear chart, employing an artificial neural network to model and predict nuclear dipole responses. We train the network on a dataset of experimentally measured dipole strengt
Externí odkaz:
http://arxiv.org/abs/2412.02876
Publikováno v:
TDR (1988-), 2016 Dec 01. 60(4), 9-9.
Externí odkaz:
http://www.jstor.org/stable/24917096
Autor:
Wang, Zhilin, Bukharin, Alexander, Delalleau, Olivier, Egert, Daniel, Shen, Gerald, Zeng, Jiaqi, Kuchaiev, Oleksii, Dong, Yi
Reward models are critical for aligning models to follow instructions, and are typically trained following one of two popular paradigms: Bradley-Terry style or Regression style. However, there is a lack of evidence that either approach is better than
Externí odkaz:
http://arxiv.org/abs/2410.01257
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
We consider divergence form operators with complex coefficients on an open subset of Euclidean space. Boundary conditions in the corresponding parabolic problem are dynamical, that is, the time derivative appears on the boundary. As a matter of fact,
Externí odkaz:
http://arxiv.org/abs/2406.09583
Autor:
Wang, Zhilin, Dong, Yi, Delalleau, Olivier, Zeng, Jiaqi, Shen, Gerald, Egert, Daniel, Zhang, Jimmy J., Sreedhar, Makesh Narsimhan, Kuchaiev, Oleksii
High-quality preference datasets are essential for training reward models that can effectively guide large language models (LLMs) in generating high-quality responses aligned with human preferences. As LLMs become stronger and better aligned, permiss
Externí odkaz:
http://arxiv.org/abs/2406.08673
The preliminary material of the monograph (arXiv:1607.03852) written by the first two authors contains two major imprecisions that necessitates a number of (in the end harmless) changes throughout the entire text. One is about identification of abstr
Externí odkaz:
http://arxiv.org/abs/2406.07570
Autor:
Shen, Gerald, Wang, Zhilin, Delalleau, Olivier, Zeng, Jiaqi, Dong, Yi, Egert, Daniel, Sun, Shengyang, Zhang, Jimmy, Jain, Sahil, Taghibakhshi, Ali, Ausin, Markel Sanz, Aithal, Ashwath, Kuchaiev, Oleksii
Aligning Large Language Models (LLMs) with human values and preferences is essential for making them helpful and safe. However, building efficient tools to perform alignment can be challenging, especially for the largest and most competent LLMs which
Externí odkaz:
http://arxiv.org/abs/2405.01481