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2212.08378
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Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Neural Information Processing Systems (NeurIPS), 2022
16 December 2022
Alex Tamkin
Margalit Glasgow
Xiluo He
Noah D. Goodman
SSL
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Papers citing
"Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning"
8 / 8 papers shown
Enhanced Pre-training of Graph Neural Networks for Million-Scale Heterogeneous Graphs
Shengyin Sun
Chen Ma
Jiehao Chen
152
0
0
14 Oct 2025
Beyond Self-Consistency: Loss-Balanced Perturbation-Based Regularization Improves Industrial-Scale Ads Ranking
Ilqar Ramazanli
Hamid Eghbalzadeh
Xiaoyi Liu
Yang Wang
Jiaxiang Fu
Kaushik Rangadurai
Sem Park
Bo Long
Xue Feng
318
1
0
05 Feb 2025
COSMOS: Cross-Modality Self-Distillation for Vision Language Pre-training
Computer Vision and Pattern Recognition (CVPR), 2024
Sanghwan Kim
Rui Xiao
Mariana-Iuliana Georgescu
Stephan Alaniz
Zeynep Akata
VLM
711
7
0
02 Dec 2024
InfoNCE: Identifying the Gap Between Theory and Practice
E. Rusak
Patrik Reizinger
Attila Juhos
Oliver Bringmann
Roland S. Zimmermann
Wieland Brendel
492
28
0
28 Jun 2024
Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning
Jihai Zhang
Xiang Lan
Xiaoye Qu
Yu Cheng
Mengling Feng
Bryan Hooi
SSL
302
5
0
19 Feb 2024
Multispectral Contrastive Learning with Viewmaker Networks
Jasmine Bayrooti
Noah D. Goodman
Alex Tamkin
248
1
0
11 Feb 2023
Task Ambiguity in Humans and Language Models
Alex Tamkin
Kunal Handa
Ava Shrestha
Noah D. Goodman
UQLM
333
24
0
20 Dec 2022
Unsupervised Learning of Visual Features by Contrasting Cluster Assignments
Mathilde Caron
Ishan Misra
Julien Mairal
Priya Goyal
Piotr Bojanowski
Armand Joulin
OCL
SSL
1.2K
4,680
0
17 Jun 2020
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