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Oct, 2024
多模态数据的受控解缠信息标准
An Information Criterion for Controlled Disentanglement of Multimodal Data
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Chenyu Wang, Sharut Gupta, Xinyi Zhang, Sana Tonekaboni, Stefanie Jegelka...
TL;DR
本研究解决了多模态表示学习中信息解缠的难题,提出了一种新的自监督学习方法——解缠自监督学习(DisentangledSSL)。该方法成功地从多个合成和真实数据集中学习到共享与特定模态的特征,并在多个下游任务中优于基线模型,具有显著的实用价值。
Abstract
multimodal
representation learning
seeks to relate and decompose information inherent in multiple modalities. By disentangling modality-specific information from information that is shared across modalities, we c
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