SOTAVerified

Ordinal Classification

Papers

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Showing 1–25 of 72 papers

TitleStatusHype
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
dlordinal: a Python package for deep ordinal classificationCode2
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
Fusing Echocardiography Images and Medical Records for Continuous Patient Stratification—0
Ordinal classification for interval-valued data and interval-valued functional dataCode0
Ordinal Classification with Distance Regularization for Robust Brain Age PredictionCode1
Performance Metrics for Probabilistic Ordinal ClassifiersCode0
Learning-to-Rank Meets Language: Boosting Language-Driven Ordering Alignment for Ordinal ClassificationCode1
Convolutional and Deep Learning based techniques for Time Series Ordinal ClassificationCode0
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Benchmark Results

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