Zobrazeno 1 - 10
of 24 463
pro vyhledávání: '"A. Veer"'
In this paper, we review several results on the zero loci of Bernstein-Sato ideals related to singularities of hypersurfaces. This is an exposition for the Frontiers of Science Awards in Mathematics presenting results from one of our articles, with h
Externí odkaz:
http://arxiv.org/abs/2408.13560
Autor:
Li, Boyi, Zhu, Ligeng, Tian, Ran, Tan, Shuhan, Chen, Yuxiao, Lu, Yao, Cui, Yin, Veer, Sushant, Ehrlich, Max, Philion, Jonah, Weng, Xinshuo, Xue, Fuzhao, Tao, Andrew, Liu, Ming-Yu, Fidler, Sanja, Ivanovic, Boris, Darrell, Trevor, Malik, Jitendra, Han, Song, Pavone, Marco
We propose Wolf, a WOrLd summarization Framework for accurate video captioning. Wolf is an automated captioning framework that adopts a mixture-of-experts approach, leveraging complementary strengths of Vision Language Models (VLMs). By utilizing bot
Externí odkaz:
http://arxiv.org/abs/2407.18908
Autor:
Ranka, Hriday, Surana, Mokshit, Kothari, Neel, Pariawala, Veer, Banerjee, Pratyay, Surve, Aditya, Sankepally, Sainath Reddy, Jain, Raghav, Lalwani, Jhagrut, Mehta, Swapneel
It is becoming cheaper to launch disinformation operations at scale using AI-generated content, in particular 'deepfake' technology. We have observed instances of deepfakes in political campaigns, where generated content is employed to both bolster t
Externí odkaz:
http://arxiv.org/abs/2406.14290
Modern motion planners for autonomous driving frequently use imitation learning (IL) to draw from expert driving logs. Although IL benefits from its ability to glean nuanced and multi-modal human driving behaviors from large datasets, the resulting p
Externí odkaz:
http://arxiv.org/abs/2405.11139
Autor:
Biswas, Abhijit, Serles, Peter, Alvarez, Gustavo A., Schimpf, Jesse, Hache, Michel, Kong, Jonathan, Demingos, Pedro Guerra, Yuan, Bo, Pieshkov, Tymofii S., Li, Chenxi, Puthirath, Anand B., Gao, Bin, Gray, Tia, Zhang, Xiang, Murukeshan, Jishnu, Vajtai, Robert, Dai, Pengcheng, Singh, Chandra Veer, Howe, Jane, Zou, Yu, Martin, Lane W., Clancy, James Patrick, Tian, Zhiting, Filleter, Tobin, Ajayan, Pulickel M.
Hexagonal boron nitride (h-BN) is brittle, however, its atomic-scale structural engineering can lead to unprecedented physical properties. Here we report the bulk synthesis of high-density crystalline h-BN solids by using high-temperature spark plasm
Externí odkaz:
http://arxiv.org/abs/2405.06007
Autor:
Patra, Braja Gopal, Lepow, Lauren A., Kumar, Praneet Kasi Reddy Jagadeesh, Vekaria, Veer, Sharma, Mohit Manoj, Adekkanattu, Prakash, Fennessy, Brian, Hynes, Gavin, Landi, Isotta, Sanchez-Ruiz, Jorge A., Ryu, Euijung, Biernacka, Joanna M., Nadkarni, Girish N., Talati, Ardesheer, Weissman, Myrna, Olfson, Mark, Mann, J. John, Charney, Alexander W., Pathak, Jyotishman
Background: Social support (SS) and social isolation (SI) are social determinants of health (SDOH) associated with psychiatric outcomes. In electronic health records (EHRs), individual-level SS/SI is typically documented as narrative clinical notes r
Externí odkaz:
http://arxiv.org/abs/2403.17199
This paper presents a hierarchical control framework that enables robust quadrupedal locomotion on a dynamic rigid surface (DRS) with general and unknown vertical motions. The key novelty of the framework lies in its higher layer, which is a discrete
Externí odkaz:
http://arxiv.org/abs/2403.16262
Autor:
Pourhassan, Behnam, Farahani, Hoda, Kazemian, Farideh, Sakallı, İzzet, Upadhyay, Sudhaker, Singh, Dharm Veer
Publikováno v:
Physics of the Dark Universe 44 (2024) 101444
In this paper, we use the holographic principle to obtain a modified metric of black holes that reproduces the exponentially corrected entropy. The exponential correction of the black hole entropy comes from non-perturbative corrections. It interpret
Externí odkaz:
http://arxiv.org/abs/2403.07972
Autor:
Li, Boyi, Wang, Yue, Mao, Jiageng, Ivanovic, Boris, Veer, Sushant, Leung, Karen, Pavone, Marco
Adapting driving behavior to new environments, customs, and laws is a long-standing problem in autonomous driving, precluding the widespread deployment of autonomous vehicles (AVs). In this paper, we present LLaDA, a simple yet powerful tool that ena
Externí odkaz:
http://arxiv.org/abs/2402.05932
Autor:
Sharma, Apoorva, Veer, Sushant, Hancock, Asher, Yang, Heng, Pavone, Marco, Majumdar, Anirudha
Inductive Conformal Prediction (ICP) provides a practical and effective approach for equipping deep learning models with uncertainty estimates in the form of set-valued predictions which are guaranteed to contain the ground truth with high probabilit
Externí odkaz:
http://arxiv.org/abs/2312.04658