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MoDE: CLIP Data Experts via Clustering
April 25, 2024, 5:44 p.m. | Jiawei Ma, Po-Yao Huang, Saining Xie, Shang-Wen Li, Luke Zettlemoyer, Shih-Fu Chang, Wen-Tau Yih, Hu Xu
cs.CL updates on arXiv.org arxiv.org
Abstract: The success of contrastive language-image pretraining (CLIP) relies on the supervision from the pairing between images and captions, which tends to be noisy in web-crawled data. We present Mixture of Data Experts (MoDE) and learn a system of CLIP data experts via clustering. Each data expert is trained on one data cluster, being less sensitive to false negative noises in other clusters. At inference time, we ensemble their outputs by applying weights determined through the …
arxiv clip clustering cs.ai cs.cl cs.cv cs.lg data experts type via
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