Zobrazeno 1 - 10
of 112 430
pro vyhledávání: '"A. Bansal"'
In this work, we study the cosmological effects of a tower of warm dark matter states on the cosmic microwave background (CMB) and on large-scale structure (LSS). For concreteness, we consider the $N$naturalness model, which is a proposed mechanism t
Externí odkaz:
http://arxiv.org/abs/2410.19224
Neural posterior estimation (NPE), a simulation-based computational approach for Bayesian inference, has shown great success in situations where posteriors are intractable or likelihood functions are treated as "black boxes." Existing NPE methods typ
Externí odkaz:
http://arxiv.org/abs/2410.19105
Autor:
Li, Jialu, Li, Yuanzhen, Wadhwa, Neal, Pritch, Yael, Jacobs, David E., Rubinstein, Michael, Bansal, Mohit, Ruiz, Nataniel
We introduce the concept of a generative infinite game, a video game that transcends the traditional boundaries of finite, hard-coded systems by using generative models. Inspired by James P. Carse's distinction between finite and infinite games, we l
Externí odkaz:
http://arxiv.org/abs/2410.18975
Four-dimensional scanning transmission electron microscopy (4D-STEM) is a powerful tool that allows for the simultaneous acquisition of spatial and diffraction information, driven by recent advancements in direct electron detector technology. Althoug
Externí odkaz:
http://arxiv.org/abs/2410.17206
Autor:
Neha, Fnu, Bansal, Arvind K.
Publikováno v:
Proceedings of the 10th World Congress on Electrical Engineering and Computer Systems and Science, Avestia Publishing, ISSN = 2369-811X, 2024
Renal tumors, especially renal cell carcinoma (RCC), show significant heterogeneity, posing challenges for diagnosis using radiology images such as MRI, echocardiograms, and CT scans. U-Net based deep learning techniques are emerging as a promising a
Externí odkaz:
http://arxiv.org/abs/2410.15472
Diffusion models have emerged as a powerful tool for image generation and denoising. Typically, generative models learn a trajectory between the starting noise distribution and the target data distribution. Recently Liu et al. (2023b) designed a nove
Externí odkaz:
http://arxiv.org/abs/2410.14949
Large language models (LLMs) are susceptible to persuasion, which can pose risks when models are faced with an adversarial interlocutor. We take a first step towards defending models against persuasion while also arguing that defense against adversar
Externí odkaz:
http://arxiv.org/abs/2410.14596
Recent advances in diffusion models have significantly enhanced their ability to generate high-quality images and videos, but they have also increased the risk of producing unsafe content. Existing unlearning/editing-based methods for safe generation
Externí odkaz:
http://arxiv.org/abs/2410.12761
Autor:
Wang, Zhaoyang, He, Weilei, Liang, Zhiyuan, Zhang, Xuchao, Bansal, Chetan, Wei, Ying, Zhang, Weitong, Yao, Huaxiu
Recent self-rewarding large language models (LLM) have successfully applied LLM-as-a-Judge to iteratively improve the alignment performance without the need of human annotations for preference data. These methods commonly utilize the same LLM to act
Externí odkaz:
http://arxiv.org/abs/2410.12735
The widespread dissemination of false information through manipulative tactics that combine deceptive text and images threatens the integrity of reliable sources of information. While there has been research on detecting fake news in high resource la
Externí odkaz:
http://arxiv.org/abs/2410.10407