Extreme Multi Label Classification


Extreme multi-label classification is the task of assigning multiple labels to a single instance from an extremely large label space.

PiPViT: Patch-based Visual Interpretable Prototypes for Retinal Image Analysis

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Jun 12, 2025
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Transformers Meet Hyperspectral Imaging: A Comprehensive Study of Models, Challenges and Open Problems

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Jun 10, 2025
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Efficient Text Encoders for Labor Market Analysis

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May 30, 2025
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Frequency-Adaptive Discrete Cosine-ViT-ResNet Architecture for Sparse-Data Vision

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May 28, 2025
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Automatic Construction of Multiple Classification Dimensions for Managing Approaches in Scientific Papers

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May 29, 2025
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MT-CYP-Net: Multi-Task Network for Pixel-Level Crop Yield Prediction Under Very Few Samples

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May 17, 2025
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Hierarchical Multi-Label Generation with Probabilistic Level-Constraint

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Apr 30, 2025
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ScarceGAN: Discriminative Classification Framework for Rare Class Identification for Longitudinal Data with Weak Prior

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May 02, 2025
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Multi-Head Encoding for Extreme Label Classification

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Dec 13, 2024
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Prototypical Extreme Multi-label Classification with a Dynamic Margin Loss

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Oct 27, 2024
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