Zobrazeno 1 - 10
of 2 280
pro vyhledávání: '"P. Vineeth"'
Autor:
Vineeth, S., Abraham, Noble P.
Charged dust is present in almost all astrophysical and laboratory plasma environments. They alter the plasma charge density and also give rise to various modes of electrostatic waves and oscillations. In this paper we study the properties of Dust Ac
Externí odkaz:
http://arxiv.org/abs/2410.20461
Autor:
Edwin, D., Mathew, Blesson, Shridharan, B., Valsan, Vineeth, Nidhi, S., Bhattacharyya, Suman, Kartha, Sreeja S., Robin, T.
Low-mass emission-line stars belong to various evolutionary stages, from pre-main-sequence young stars to evolved stars. In this work, we present a catalog of late-type (F0 to M9) emission-line stars from the LAMOST Data Release 6. Using the scipy pa
Externí odkaz:
http://arxiv.org/abs/2410.17753
This study investigates the orbital decay and subsequent reentries of 12 Starlink satellites from 16 April to 15 May 2024. By examining Two-Line Element data, we observed a significant increase in orbital decay following the geomagnetic storm on 10 M
Externí odkaz:
http://arxiv.org/abs/2410.16254
Despite the importance of developing generative AI models that can effectively resist scams, current literature lacks a structured framework for evaluating their vulnerability to such threats. In this work, we address this gap by constructing a bench
Externí odkaz:
http://arxiv.org/abs/2410.13893
Autor:
Yu, Xiao, Peng, Baolin, Vajipey, Vineeth, Cheng, Hao, Galley, Michel, Gao, Jianfeng, Yu, Zhou
Autonomous agents have demonstrated significant potential in automating complex multistep decision-making tasks. However, even state-of-the-art vision-language models (VLMs), such as GPT-4o, still fall short of human-level performance, particularly i
Externí odkaz:
http://arxiv.org/abs/2410.02052
Autor:
Choi, Sunjin, Jain, Diksha, Kim, Seok, Krishna, Vineeth, Lee, Eunwoo, Minwalla, Shiraz, Patel, Chintan
Charged Black holes in $AdS_5 \times S^5$ suffer from superradiant instabilities over a range of energies. Hairy black hole solutions (constructed within gauged supergravity) have previously been proposed as endpoints to this instability. We demonstr
Externí odkaz:
http://arxiv.org/abs/2409.18178
Detecting and measuring confounding effects from data is a key challenge in causal inference. Existing methods frequently assume causal sufficiency, disregarding the presence of unobserved confounding variables. Causal sufficiency is both unrealistic
Externí odkaz:
http://arxiv.org/abs/2409.17840
Autor:
Mekala, Anmol, Dorna, Vineeth, Dubey, Shreya, Lalwani, Abhishek, Koleczek, David, Rungta, Mukund, Hasan, Sadid, Lobo, Elita
Machine unlearning aims to efficiently eliminate the influence of specific training data, known as the forget set, from the model. However, existing unlearning methods for Large Language Models (LLMs) face a critical challenge: they rely solely on ne
Externí odkaz:
http://arxiv.org/abs/2409.13474
Autor:
Chavan, Aneesh, Agrawal, Vaibhav, Bhat, Vineeth, Chittawar, Sarthak, Srivastava, Siddharth, Arora, Chetan, Krishna, K Madhava
Re-identification (ReID) is a critical challenge in computer vision, predominantly studied in the context of pedestrians and vehicles. However, robust object-instance ReID, which has significant implications for tasks such as autonomous exploration,
Externí odkaz:
http://arxiv.org/abs/2409.12002
Autor:
Ramachandran, Rahul, Kulkarni, Tejal, Sharma, Charchit, Vijaykeerthy, Deepak, Balasubramanian, Vineeth N
Evaluating models and datasets in computer vision remains a challenging task, with most leaderboards relying solely on accuracy. While accuracy is a popular metric for model evaluation, it provides only a coarse assessment by considering a single mod
Externí odkaz:
http://arxiv.org/abs/2409.04041