← Back to all news
arXiv Computer Vision October 21, 2026 By Jiyoung Lim, Jee-Hyong Lee

CILA: Confusion-based Instance-wise Logit Adjustment for Long-Tailed Recognition

Read the original on arXiv Computer Vision →

The Flow has not summarised this story yet — read it at arXiv Computer Vision.

  • benchmarks

One email a morning, machine-written

One email a day, machine-written, one click to leave. We never share your address.

Related stories

Hugging Face Trending Papers
5d ago

CILA: Confusion-based Instance-wise Logit Adjustment for Long-Tailed Recognition

Real-world datasets are inherently class-imbalanced, leading models to favor majority classes and struggle with minority ones. Existing logit adjustment methods address this by modifying logits based...

benchmarks
More like this →
arXiv Machine Learning
4d ago

Using Set Learning to Improve Set-Valued Classifiers on Long-tailed Data

arXiv:2610.27443v1 Announce Type: new Abstract: Set-valued classification (SVC) offers a practical approach to communicating uncertainty while maintaining accuracy by predicting variable-sized sets p...

By Kevin Kasa, Scott C. Lowe, Graham W. Taylor
More like this →
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...

By Yue Cheng, Jiajun Zhang, Xiaohui Gao, Weiwei Xing, Zhanxing Zhu
efficiencybenchmarkssafety
More like this →
arXiv Machine Learning
Aug 18

Free-Flow Class-Incremental Learning: Towards Robust CIL under Variable Class Arrivals

arXiv:2604. 02765v2 Announce Type: replace Abstract: Class-incremental learning (CIL) is commonly evaluated under predefined schedules with fixed or nearly equal class increments, leaving irregular class-arrival scenarios underexplored.

By Zhiming Xu, Baile Xu, Jian Zhao, Furao Shen, Suorong Yang
safety
More like this →
arXiv Machine Learning
Sep 16

Mini-batch Sampling Strategies for Long-Tailed Image Classification: An Empirical Study on CIFAR-100-LT

arXiv:2609.16365v1 Announce Type: cross Abstract: Real-world datasets often exhibit long-tailed class distributions, where a few head classes contain a large number of training samples while a large...

By Siyu Yuan
computer-visionsafety
More like this →
arXiv Machine Learning
Aug 21

Neural Prior Estimation: Learning Class Priors from Latent Representations

arXiv:2602. 17853v2 Announce Type: replace Abstract: Logit adjustment corrects class imbalance using the empirical class prior.

By Masoud Yavari, Payman Moallem
More like this →
About Pricing API Newsletter Sources Privacy Terms Refunds Accessibility Provider info Contact RSS

The Flow links to publishers and never republishes their articles. Summaries are machine-generated.

v1.1.0 · 5f852ea