repoGitHubTrust 82 · PrimaryPublished 6d agoLive · 5d ago
CVHub520/X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
Implements
paperBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic PotentialspaperAdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object CountingpaperHERMES: A Multi-Granularity Labeling Substrate for Pre-training Data MixturespaperTRCGL-Net: A Long-Tailed Multi-Label Chest X-Ray Classification Framework with Generative Data Augmentation and Label Co-Occurrence ModelingpaperLow-cost concept-based localized explanations: How far can we get with training-free approaches?
Related across the graph
paperHERMES: A Multi-Granularity Labeling Substrate for Pre-training Data MixturespaperBeyond Adam: SOAP and Muon for Faster, Label-Efficient Training of Machine Learning Interatomic PotentialspaperAdaCount: Training-Free Similarity-Guided Spatial and Feature Adaptation for Zero-Shot Object CountingpaperTRCGL-Net: A Long-Tailed Multi-Label Chest X-Ray Classification Framework with Generative Data Augmentation and Label Co-Occurrence ModelingpaperLow-cost concept-based localized explanations: How far can we get with training-free approaches?