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pro vyhledávání: '"Goyal, Yash"'
Autor:
Mañas, Oscar, Rodriguez, Pau, Ahmadi, Saba, Nematzadeh, Aida, Goyal, Yash, Agrawal, Aishwarya
Large pre-trained models have proved to be remarkable zero- and (prompt-based) few-shot learners in unimodal vision and language tasks. We propose MAPL, a simple and parameter-efficient method that reuses frozen pre-trained unimodal models and levera
Externí odkaz:
http://arxiv.org/abs/2210.07179
The ability to integrate context, including perceptual and temporal cues, plays a pivotal role in grounding the meaning of a linguistic utterance. In order to measure to what extent current vision-and-language models master this ability, we devise a
Externí odkaz:
http://arxiv.org/abs/2203.15867
Autor:
Periwal, Neha, Arora, Pooja, Thakur, Ananya, Agrawal, Lakshay, Goyal, Yash, Rathore, Anand S., Anand, Harsimrat Singh, Kaur, Baljeet, Sood, Vikas
Publikováno v:
In Heliyon 30 August 2024 10(16)
Music, an integral part of our lives, which is not only a source of entertainment but plays an important role in mental well-being by impacting moods, emotions and other affective states. Music preferences and listening strategies have been shown to
Externí odkaz:
http://arxiv.org/abs/2009.13685
Musical preferences have been considered a mirror of the self. In this age of Big Data, online music streaming services allow us to capture ecologically valid music listening behavior and provide a rich source of information to identify several user-
Externí odkaz:
http://arxiv.org/abs/2007.13159
Akademický článek
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While Visual Question Answering (VQA) models continue to push the state-of-the-art forward, they largely remain black-boxes - failing to provide insight into how or why an answer is generated. In this ongoing work, we propose addressing this shortcom
Externí odkaz:
http://arxiv.org/abs/1911.06352
How can we understand classification decisions made by deep neural networks? Many existing explainability methods rely solely on correlations and fail to account for confounding, which may result in potentially misleading explanations. To overcome th
Externí odkaz:
http://arxiv.org/abs/1907.07165
In this work, we develop a technique to produce counterfactual visual explanations. Given a 'query' image $I$ for which a vision system predicts class $c$, a counterfactual visual explanation identifies how $I$ could change such that the system would
Externí odkaz:
http://arxiv.org/abs/1904.07451
Problems at the intersection of vision and language are of significant importance both as challenging research questions and for the rich set of applications they enable. However, inherent structure in our world and bias in our language tend to be a
Externí odkaz:
http://arxiv.org/abs/1612.00837