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Improving out-of-distribution (OOD) generalization during in-distribution (ID) adaptation is a primary goal of robust fine-tuning of zero-shot models beyond naive fine-tuning.
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Fine-tuning can distort pretrained features and underperform out-of-distribution
Ananya Kumar, Aditi Raghunathan, Robbie Jones, Tengyu Ma, and Percy Liang · 2022
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Optimal representations for covariate shift
Yangjun Ruan, Yann Dubois, and Chris J Maddison · 2022
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Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, et al · 2022
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Robust calibration with multi-domain temperature scaling
Yaodong Yu, Stephen Bates, Yi Ma, and Michael Jordan · 2022
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Scaling vision transformers to 22 billion parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, et al · 2023
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Finetune like you pretrain: Improved finetuning of zero-shot vision models
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A simple framework for contrastive learning of visual representations
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Calibration of neural networks using splines
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Calibrating deep neural networks using focal loss
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Calibrated prediction with covariate shift via unsupervised domain adaptation
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Revisiting knowledge distillation via label smoothing regularization
Li Yuan, Francis EH Tay, Guilin Li, Tao Wang, and Jiashi Feng · 2020
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The power of contrast for feature learning: A theoretical analysis
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Sample-dependent adaptive temperature scaling for improved calibration
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Surgical fine-tuning improves adaptation to distribution shifts
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Anchor-based robust finetuning of vision-language models
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The platonic representation hypothesis
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Context-aware robust fine-tuning
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DINOv2: Learning robust visual features without supervision
Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel HAZIZA, Francisco Massa, Alaaeldin El-Nouby, Mido Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2024
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