Hugging Face Trending Papers
Shortcut-Resistant CAM Distillation for Long-Tailed Recognition
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arXiv Machine Learning
Oct 22
Shortcut-Resistant CAM Distillation for Long-Tailed Recognition
The paper introduces Shortcut-Resistant CAM Distillation (SRCD), a plug‑and‑play framework that mitigates shortcut learning in long‑tailed recognition tasks. SRCD transfers object‑focused explanations from head classes to tail classes by aggregating Class Activation Maps (CAMs) into a shortcut‑resistant teacher and distilling it to tail‑class CAMs. The authors provide a theoretical analysis of shortcut reliance in CAM space and demonstrate consistent improvements over strong baselines on long‑tailed benchmarks.
arXiv Computer Vision
Sep 30
OFBD: Object-Focused Background Debiasing for Long-Tailed Learning
arXiv:2609.37331v1 Announce Type: new Abstract: Balancing performance trade-offs on long-tailed data distributions remains a long-standing challenge in visual recognition. Existing methods mainly imp...
Hugging Face Trending Papers
Sep 29
OFBD: Object-Focused Background Debiasing for Long-Tailed Learning
Balancing performance trade-offs on long-tailed data distributions remains a long-standing challenge in visual recognition. Existing methods mainly improve tail classes through re-balancing, represent...
arXiv Computer Vision
Oct 7
Unsupervised Long-Tailed Adaptation of Vision-Language Models
arXiv:2610.07903v1 Announce Type: new Abstract: Adapting vision-language models to downstream tasks has achieved remarkable success by leveraging pseudo-labels generated from unlabeled data. Existing...
arXiv AI
Sep 1
Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning
arXiv:2608.30699v1 Announce Type: cross Abstract: Long-tailed distributions are prevalent in real-world semi-supervised learning (SSL), where pseudo-labels tend to favor majority classes, leading to...
arXiv AI
Oct 2
Where-OPD: Spatially Guided On-Policy Self-Distillation of MLLMs with Synthetic Scenes
arXiv:2610.02117v1 Announce Type: cross Abstract: On-policy self-distillation has recently emerged as an effective approach for improving language-model reasoning by supervising students with a froze...