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[Survey] Awesome List of Mixup Augmentation and Beyond (https://arxiv.org/abs/2409.05202)

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IntroductionSample Mixup Policies in SLOptimizing CalibrationArea-basedLoss ObjectRandom Label PoliciesOptimizing Mixing RatioGenerating LabelAttention ScoreSaliency TokenSelf-Supervised LearningCV Downstream TasksTraining ParadigmsBeyond VisionAnalysis and TheoremSurveyBenchmarkRelated Datasets LinkRelated Project

Use this list with your AI agent

Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:

"Show me contrastive learning resources from awesome-mixup"

Installation instructions →

What's inside

Related Datasets Link

Sample Mixup Policies in SL

Self-Supervised Learning

  • PaperContrastive Learning

  • PaperContrastive Learning

  • PaperContrastive Learning

  • PaperContrastive Learning

  • PaperContrastive Learning

  • PaperContrastive Learning

Area-based

Optimizing Calibration

Showing a sample of 292 resources. View the full list on GitHub →