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title
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Vivek Ramanujan
updated
2025-12-14 13:43:08
raw text
Forward Compatible Training for Representation Learning Vivek Ramanujan , Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, Hadi Pouransari In Proceedings at CVPR , 2022 In real world visual retrieval systems, the embedding model is consistently updated. This requires embeddings for all images in the gallery to be recomputed for every new model, an expensive process known as backfilling. We present a method for forward compatible training (FCT) in which we prepare for the future version of a model by saving cheap auxiliary information about the present training task. We show empirically that this improves performance on model compatibility on common largescale datasets (ImageNet, Places-365, VGGFace2). Code Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent Will Merrill, Vivek Ramanujan , Yoav Goldberg, Roy Schwartz, Noah Smith In Proceedings at EMNLP , (Oral) 2022 The capacity of neural networks like ...
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