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Contrastive Data and Learning for Natural Language Processing
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Contrastive Data and Learning for Natural Language Processing
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2026-01-11 14:53:40
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Contrastive Data and Learning for Natural Language Processing Contrastive Data and Learning for Natural Language Processing Tutorial at NAACL 2022 at Seattle, WA. July 10 - July 15, 2022 Tutorial Time and Location Location: Columbia A + Zoom Time: 2:00-5:30pm PDT, July 10, 2022 Zoom Q&A sessions: 1:30 - 2:00pm, 6:00 - 6:45pm PDT, July 10, 2022 Tutorial Materials Tutorial abstract in the conference proceeding [PDF] Tutorial slides [slides] Tutorial video [video] Paper reading list of contrastive learning for NLP [Github] Abstract Current NLP models heavily rely on effective representation learning algorithms. Contrastive learning is one such technique to learn an embedding space such that similar data sample pairs have close representations while dissimilar samples stay far apart from each other. It can be used in supervised or unsupervised settings using different loss functions to produce task-specific or general-purpose...
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