Zobrazeno 1 - 10
of 47
pro vyhledávání: '"Mathur, Puneet"'
Autor:
Biswas, Sanket, Jain, Rajiv, Morariu, Vlad I., Gu, Jiuxiang, Mathur, Puneet, Wigington, Curtis, Sun, Tong, Lladós, Josep
While the generation of document layouts has been extensively explored, comprehensive document generation encompassing both layout and content presents a more complex challenge. This paper delves into this advanced domain, proposing a novel approach
Externí odkaz:
http://arxiv.org/abs/2406.08354
Autor:
Mittal, Trisha, Mathur, Puneet, Chandra, Rohan, Bhatt, Apurva, Gupta, Vikram, Mukherjee, Debdoot, Bera, Aniket, Manocha, Dinesh
We present a computational approach for estimating emotion contagion on social media networks. Built on a foundation of psychology literature, our approach estimates the degree to which the perceivers' emotional states (positive or negative) start to
Externí odkaz:
http://arxiv.org/abs/2207.07165
Autor:
Gupta, Vikram, Mittal, Trisha, Mathur, Puneet, Mishra, Vaibhav, Maheshwari, Mayank, Bera, Aniket, Mukherjee, Debdoot, Manocha, Dinesh
We present 3MASSIV, a multilingual, multimodal and multi-aspect, expertly-annotated dataset of diverse short videos extracted from short-video social media platform - Moj. 3MASSIV comprises of 50k short videos (20 seconds average duration) and 100K u
Externí odkaz:
http://arxiv.org/abs/2203.14456
We present Affect2MM, a learning method for time-series emotion prediction for multimedia content. Our goal is to automatically capture the varying emotions depicted by characters in real-life human-centric situations and behaviors. We use the ideas
Externí odkaz:
http://arxiv.org/abs/2103.06541
We present a new approach, that we call AdaGTCN, for identifying human reader intent from Electroencephalogram~(EEG) and Eye movement~(EM) data in order to help differentiate between normal reading and task-oriented reading. Understanding the physiol
Externí odkaz:
http://arxiv.org/abs/2102.11922
Autor:
Anand, Gyanesh, Gautam, Akash, Mathur, Puneet, Mahata, Debanjan, Shah, Rajiv Ratn, Sawhney, Ramit
Twitter is a social media platform where users express opinions over a variety of issues. Posts offering grievances or complaints can be utilized by private/ public organizations to improve their service and promptly gauge a low-cost assessment. In t
Externí odkaz:
http://arxiv.org/abs/2001.09215
Autor:
Gautam, Akash, Mathur, Puneet, Gosangi, Rakesh, Mahata, Debanjan, Sawhney, Ramit, Shah, Rajiv Ratn
In this paper, we present a dataset containing 9,973 tweets related to the MeToo movement that were manually annotated for five different linguistic aspects: relevance, stance, hate speech, sarcasm, and dialogue acts. We present a detailed account of
Externí odkaz:
http://arxiv.org/abs/1912.06927
Autor:
Anghelina, Mirela, Naughton, Michelle J., Zhao, Qiuhong, Ruppert, Amy S., Neal, Jasmine, Rogers, Kerry A., Blachly, James S., Lozanski, Gerard, Bhat, Seema A., Kraut, Eric, Epperla, Narendranath, Mathur, Puneet, Zent, Clive S., Banerji, Versha, Dearden, Claire, Hutchinson, Terri, Grever, Michael, Andritsos, Leslie A.
Publikováno v:
In Leukemia Research September 2022 120