Zobrazeno 1 - 10
of 27 124
pro vyhledávání: '"Shapira, A"'
Autor:
Shapira, Chen, Rosenbaum, Dan
Models that adapt their predictions based on some given contexts, also known as in-context learning, have become ubiquitous in recent years. We propose to study the behavior of such models when data is contaminated by noise. Towards this goal we use
Externí odkaz:
http://arxiv.org/abs/2411.01670
Autor:
Shoshan, Yoel, Raboh, Moshiko, Ozery-Flato, Michal, Ratner, Vadim, Golts, Alex, Weber, Jeffrey K., Barkan, Ella, Rabinovici-Cohen, Simona, Polaczek, Sagi, Amos, Ido, Shapira, Ben, Hazan, Liam, Ninio, Matan, Ravid, Sivan, Danziger, Michael M., Morrone, Joseph A., Suryanarayanan, Parthasarathy, Rosen-Zvi, Michal, Hexter, Efrat
Drug discovery typically consists of multiple steps, including identifying a target protein key to a disease's etiology, validating that interacting with this target could prevent symptoms or cure the disease, discovering a small molecule or biologic
Externí odkaz:
http://arxiv.org/abs/2410.22367
Remote control of robotic systems, also known as teleoperation, is crucial for the development of autonomous vehicle (AV) technology. It allows a remote operator to view live video from AVs and, in some cases, to make real-time decisions. The effecti
Externí odkaz:
http://arxiv.org/abs/2410.19791
Autor:
Shapira, Eilam, Madmon, Omer, Reinman, Itamar, Amouyal, Samuel Joseph, Reichart, Roi, Tennenholtz, Moshe
Large Language Models (LLMs) show significant potential in economic and strategic interactions, where communication via natural language is often prevalent. This raises key questions: Do LLMs behave rationally? Can they mimic human behavior? Do they
Externí odkaz:
http://arxiv.org/abs/2410.05254
Training large language models (LLMs) for external tool usage is a rapidly expanding field, with recent research focusing on generating synthetic data to address the shortage of available data. However, the absence of systematic data quality checks p
Externí odkaz:
http://arxiv.org/abs/2409.16341
Autor:
Vyas, Nikhil, Morwani, Depen, Zhao, Rosie, Shapira, Itai, Brandfonbrener, David, Janson, Lucas, Kakade, Sham
There is growing evidence of the effectiveness of Shampoo, a higher-order preconditioning method, over Adam in deep learning optimization tasks. However, Shampoo's drawbacks include additional hyperparameters and computational overhead when compared
Externí odkaz:
http://arxiv.org/abs/2409.11321
We discuss the relaxation time (inverse spectral gap) of the one dimensional $O(N)$ model, for all $N$ and with two types of boundary conditions. We see how its low temperature asymptotic behavior is affected by the topology. The combination of the s
Externí odkaz:
http://arxiv.org/abs/2407.12610
The unsupervised task of Joint Alignment (JA) of images is beset by challenges such as high complexity, geometric distortions, and convergence to poor local or even global optima. Although Vision Transformers (ViT) have recently provided valuable fea
Externí odkaz:
http://arxiv.org/abs/2407.11850
Shampoo, a second-order optimization algorithm which uses a Kronecker product preconditioner, has recently garnered increasing attention from the machine learning community. The preconditioner used by Shampoo can be viewed either as an approximation
Externí odkaz:
http://arxiv.org/abs/2406.17748
Various tasks, such as summarization, multi-hop question answering, or coreference resolution, are naturally phrased over collections of real-world documents. Such tasks present a unique set of challenges, revolving around the lack of coherent narrat
Externí odkaz:
http://arxiv.org/abs/2406.16086