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- 1Efird, Cory
- 1Fahim, Abrar
- 1Hashemzadeh, Maryam
- 1Lan, Qingfeng
- 1Mullick, Dhruv
- 1Peet-Pare, Garnet L.
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- 4Machine Learning
- 2Contrastive Learning
- 2Neuroscience
- 2Reinforcement Learning
- 2Representation Learning
- 1AI
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The Contrastive Gap: A New Perspective on the ‘Modality Gap’ in Multimodal Contrastive Learning
DownloadFall 2024
Learning jointly from images and texts using contrastive pre-training has emerged as an effective method to train large-scale models with a strong grasp of semantic image concepts. For instance, CLIP, pre-trained on a large corpus of web data, excels in tasks like zero-shot image classification,...
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