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Ordinal Classification

Papers

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Showing 1–25 of 72 papers

TitleStatusHype
A simple squared-error reformulation for ordinal classificationCode3
dlordinal: a Python package for deep ordinal classificationCode2
Ultra Fast Deep Lane Detection with Hybrid Anchor Driven Ordinal ClassificationCode2
Ordinal Classification with Distance Regularization for Robust Brain Age PredictionCode1
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal ClassificationCode1
CSAW-M: An Ordinal Classification Dataset for Benchmarking Mammographic Masking of CancerCode1
Real-Time Multi-Level Neonatal Heart and Lung Sound Quality Assessment for Telehealth ApplicationsCode1
Supervised Contrastive Learning for Ordinal Engagement Measurement—0
Multimodal Assessment of Classroom Discourse Quality: A Text-Centered Attention-Based Multi-Task Learning Approach—0
AI-Assisted Decision-Making for Clinical Assessment of Auto-Segmented Contour Quality—0
Enhancing Depression Detection via Question-wise Modality FusionCode0
Trust Modeling in Counseling Conversations: A Benchmark Study—0
CLOC: Contrastive Learning for Ordinal Classification with Multi-Margin N-pair Loss—0
Generative Regression Based Watch Time Prediction for Short-Video Recommendation—0
From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking—0
Splitting criteria for ordinal decision trees: an experimental studyCode0
LAMPO: Large Language Models as Preference Machines for Few-shot Ordinal Classification—0
Improving the classification of extreme classes by means of loss regularisation and generalised beta distributions—0
DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images—0
Optimizing Automatic Speech Assessment: W-RankSim Regularization and Hybrid Feature Fusion Strategies—0
Exploring Ordinality in Text Classification: A Comparative Study of Explicit and Implicit Techniques—0
Conformal Risk Control for Ordinal ClassificationCode0
Distribution-free Conformal Prediction for Ordinal Classification—0
Improved Text Emotion Prediction Using Combined Valence and Arousal Ordinal Classification—0
Distilling Privileged Multimodal Information for Expression Recognition using Optimal Transport—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ResNet-18Mean absolute error2.56—Unverified