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Sharpness-Aware Minimization

142 papers tagged archive 2025-07-28

Introduced by Pierre Foret et al. in Sharpness-Aware Minimization for Efficiently Improving Generalization

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Sharpness-Aware Minimization, or SAM, is a procedure that improves model generalization by simultaneously minimizing loss value and loss sharpness. SAM functions by seeking parameters that lie in neighborhoods having uniformly low loss value (rather than parameters that only themselves have low loss value).

PaperSource

Papers archive 2025-07-28

30 shown of 142, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 115 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Image Classification19
image-classification13
Data Augmentation10
Domain Generalization10
Federated Learning8
model7
Semantic Segmentation6
Computational Efficiency5
Quantization5
Segmentation5
Deep Learning4
Adversarial Robustness3
Attribute3
Classification3
Image Segmentation3
Language Modeling3
Language Modelling3
Long-tail Learning3
Node Classification3
Out-of-Distribution Detection3

Usage over time archive 2025-07-28

Papers per year tagged with Sharpness-Aware Minimization: 2020 to 2025, peak 47 47 0 2020: 1 paper 2020 2021: 10 papers 2021 2022: 27 papers 2022 2023: 34 papers 2023 2024: 47 papers 2024 2025: 23 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (142 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Optimization

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