Zobrazeno 1 - 10
of 259 655
pro vyhledávání: '"Friedman, A. A."'
Autor:
Gundavarapu, Nitesh Bharadwaj, Friedman, Luke, Goyal, Raghav, Hegde, Chaitra, Agustsson, Eirikur, Waghmare, Sagar M., Sirotenko, Mikhail, Yang, Ming-Hsuan, Weyand, Tobias, Gong, Boqing, Sigal, Leonid
Video understanding has witnessed significant progress with recent video foundation models demonstrating strong performance owing to self-supervised pre-training objectives; Masked Autoencoders (MAE) being the design of choice. Nevertheless, the majo
Externí odkaz:
http://arxiv.org/abs/2411.13683
We introduce the notions of weighted extremal K{\"a}hler twins together with the related notion of extremal Sasaki twins. In the K\"ahler setting this leads to a generalization of the twinning phenomenon appearing among LeBrun's strongly Hermitian so
Externí odkaz:
http://arxiv.org/abs/2411.13502
Autor:
Friedman, Eliahu, Gal, Avraham
This work is a sequel to our two 2023 publications [PLB 837 137669, NPA 1039 122725] where fitting 14 1$s_\Lambda$ and 1$p_\Lambda$ single-particle binding energies in hypernuclei across the periodic table led to a well-defined $\Lambda$-nucleus opti
Externí odkaz:
http://arxiv.org/abs/2411.11751
Large language models can absorb a massive amount of knowledge through pretraining, but pretraining is inefficient for acquiring long-tailed or specialized facts. Therefore, fine-tuning on specialized or new knowledge that reflects changes in the wor
Externí odkaz:
http://arxiv.org/abs/2411.07175
Autor:
Friedman, Scott E., Benkler, Noam, Mosaphir, Drisana, Rye, Jeffrey, Schmer-Galunder, Sonja M., Goldwater, Micah, McLure, Matthew, Wheelock, Ruta, Gottlieb, Jeremy, Goldman, Robert P., Miller, Christopher
Large language models (LLMs) generate diverse, situated, persuasive texts from a plurality of potential perspectives, influenced heavily by their prompts and training data. As part of LLM adoption, we seek to characterize - and ideally, manage - the
Externí odkaz:
http://arxiv.org/abs/2411.05040
Autor:
Cai, Jinjin, Wang, Ruiqi, Zhao, Dezhong, Yuan, Ziqin, McKenna, Victoria, Friedman, Aaron, Foot, Rachel, Storey, Susan, Boente, Ryan, Vhaduri, Sudip, Min, Byung-Cheol
Audio-based disease prediction is emerging as a promising supplement to traditional medical diagnosis methods, facilitating early, convenient, and non-invasive disease detection and prevention. Multimodal fusion, which integrates features from variou
Externí odkaz:
http://arxiv.org/abs/2410.09289
We introduce a framework that allows for the exact analytic treatment of quantum dynamics subject to coherent noise. The noise is modeled via unitary evolution under a Hamiltonian drawn from a random-matrix ensemble for arbitrary Hilbert-space dimens
Externí odkaz:
http://arxiv.org/abs/2410.07321
Light cone selection effects on cosmic observables must be precisely accounted for in the next generation of surveys, including the Dark Energy Spectroscopic Instrument (DESI) survey. This will allow us to correctly model the data and extract subtle
Externí odkaz:
http://arxiv.org/abs/2410.04705
In "Embers of Autoregression" (McCoy et al., 2023), we showed that several large language models (LLMs) have some important limitations that are attributable to their origins in next-word prediction. Here we investigate whether these issues persist w
Externí odkaz:
http://arxiv.org/abs/2410.01792
Autor:
Friedman, George
Publikováno v:
Horizons: Journal of International Relations and Sustainable Development, 2024 Oct 01(28), 38-47.
Externí odkaz:
https://www.jstor.org/stable/48794577
