Ordinal Regression

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4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

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Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models
Oct 6, 2026Yujie Chen, Antik Chakraborty, Anindya BhadraPreference Learning Ordinal Regression
Department of Statistics Purdue University
More Choices, Fewer Decisions: Ordinal-Scale Bias in JEV-like Direct-Decision Models
Sep 30, 2026Tianxiang Gao, Jinzhe Li, Zhiyuan Li +2LLM Evaluation Ordinal Regression
School of Artificial Intelligence, Jilin University · College of Software, Jilin University · International Center of Future Science, Jilin University +1
UO-FIE: Combining Exact-Label Supervision with Graded Utility for Factivity Inference
Sep 23, 2026Xinchen XiaoOrdinal Regression Classification
Xinjiang University
HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology
Sep 14, 2026Afshin Bozorgpour, Peter Schüffler, Edgar Jost +1Computational Pathology Hierarchical Classification
Faculty of Informatics and Data Science, University of Regensburg, Germany · Institute of Pathology, TUM School of Medicine and Health, Technical University of Munich, Germany · Munich Center for Machine Learning, Germany +4
Adaptive Margin Ordinal Loss: Penalizing Center-Class Hedging in Ordinal Classification
Sep 12, 2026Manisha KandelOrdinal Regression Adaptive Loss Weighting
Data Science Institute & Department of Civil, Construction & Environmental Engineering University of Delaware Newark, DE, USA
MAOL: Morphology-Aware Ordinal Learning for Fine-Grained Industrial Defect Severity Grading
Sep 2, 2026Zhaoyang Wang, Haiyong Chen, Binyi Su +4Industrial Inspection Ordinal Regression
Hebei University of Technology Tianjin, China · Hunan University Changsha, China · Yingli Energy Development Co. Ltd Baoding, China
Few-Shot Ordinal Learning for Day-Wise Freshness Estimation with Hyperspectral Fish Images
Aug 12, 2026Kazi Nabiul Alam, Pooneh Bagheri Zadeh, Akbar Sheikh-AkbariFew-Shot Learning Hyperspectral Imaging
School of Built Environment, Engineering and Computing, Leeds Beckett University, Leeds, United Kingdom.
Gaussian Meta-Space Augmentation for Stacking Ensembles in Multimodal IPMN Risk Stratification
Aug 11, 2026Max A. Nelson, Eminenur Sen Tasci, Zhixiang Wang +12Ensemble Learning Ordinal Regression
Machine & Hybrid Intelligence Lab, Department of Radiology, Northwestern University, Chicago, IL, USA · Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA · Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey +2
Unimodality-Promoting Regularized Learning for Ordinal Regression
Aug 8, 2026Ryoya YamasakiOrdinal Regression
DisMix: Order-Aware Mixup for Medical Imaging via Disentangling Ordinal and Non-Ordinal Features
Aug 5, 2026Dileepa Pitawela, Gustavo Carneiro, Hsiang-Ting ChenDisentangled Representation Learning Data Augmentation
1AIML, Adelaide University, Australia · 2CVSSP, University of Surrey, UK
D3O: Dynamic Distribution Distillation for Ordinal Regression
Jul 26, 2026Chunlai Dong, Yaojun Hu, Yuyang Xu +2Label Distribution Learning Ordinal Regression
Zhejiang University Hangzhou, China
ADABORD: a novel AdaBoost approach for ordinal classification
Jul 23, 2026Rafael Ayllón-Gavilán, Francisco José Martínez-Estudillo, David Guijo-Rubio +2Ensemble Learning Ordinal Regression
Department of Clinical-Epidemiological Research in Primary Care, IMIBIC, Avda. Menéndez Pidal S/N, Córdoba, 14004, Spain · Programa de doctorado en Computación Avanzada, Energía y Plasmas, Universidad de Córdoba, Campus de Rabanales, Ctra. N-IVa, Km. 396, Córdoba, 14071, Spain · Departmento de Ciencia de la Computación e Inteligencia Artificial, Universidad de Córdoba, Campus de Rabanales, Ctra. N-IVa, Km. 396, Córdoba, 14071. +2
An efficient adaptive dimension selection algorithm for multidimensional probit graded response models
Jul 20, 2026Yu Zhou, Yincai Tang, Bin Lv +1Latent Variable Models Bayesian Inference
1KLATASDS-MOE 1School of Statistics, East China Normal University, Shanghai, 200062, China · 2Zhiyuan School of Liberal Arts,Beijing Institute of Petrochemical Technology,Beijing 102617, China
Application of machine learning to monster level prediction in tabletop RPG game design
Jul 10, 2026Jolanta Śliwa, Jakub AdamczykOrdinal Regression Tabular Prediction
Faculty of Computer Science, AGH University of Krakow, Cracow, Poland
Contrastive Order Learning: A General Framework for Ordinal Regression
Jul 9, 2026Chaewon Lee, BeomJun Shim, Kwang Pyo Choi +1Contrastive Learning Ordinal Regression
School of Electrical Engineering, Korea University, Seoul, Korea · Samsung Electronics, Seoul, Korea
Stochastic Order Learning: An Approach to Rank Estimation Using Noisy Data
Jul 9, 2026Chaewon Lee, Seon-Ho Lee, Chang-Su KimLearning to Rank Noisy-Label Learning
School of Electrical Engineering, Korea University, Seoul, Korea · Amazon AGI, Seattle, USA
KOAL: Knowledge-Driven Prostate Cancer Grading with Ordinal-Aware Learning
Jul 7, 2026Zheng Guo, Jiaqi Cui, Haocheng Xiong +5Medical Image Classification Ordinal Regression
School of Computer Science, Sichuan University, China · China Mobile (Suzhou) Software Technology Company Limited, China · Shanghai Changhai Hospital, Naval Medical University, China +1
PrISM-IQA: Image Quality Assessment Made Practical for Smartphone Photography
Jun 30, 2026Shuyan Zhai, Jiaqi He, Weixia Zhang +4Ordinal Regression Image Quality Assessment
Department of Computer Science, City University of Hong Kong · School of Computer Science, Institute of AI, Shanghai Jiao Tong University · OPPO Research Institute +1
LOPA: Enhancing Spoken Language Assessment via Latent Ordinal Prototype Alignment
Jun 30, 2026Hong-Yun Lin, Fu-An Chao, Bi-Cheng Yan +1Prototype Learning Ordinal Regression
National Taiwan Normal University
Deep Neural Networks with Ordinal Loss for Medical Applications
Jun 24, 2026Tal Dvora, Rotem Haba, Gonen SingerCost-Sensitive Learning Ordinal Regression
Bar-Ilan University Ramat Gan, Israel
Reliable Conformal Prediction for Ordinal Classification Using the Ranked Probability Score
Jun 23, 2026Stefan Haas, Luca Killmaier, Alireza Javanmardi +1Conformal Prediction Ordinal Regression
Institute of Informatics, LMU Munich, Munich, Germany · BMW Group, Munich, Germany · Munich Center for Machine Learning (MCML), Munich, Germany +1
HypOProto: Hyperbolic Ordinal Prototypes for Left Ventricular Filling Pressure Classification
Jun 18, 2026Victoria Wu, Nima Hashemi, Hooman Vaseli +3Prototype-Based Classification Echocardiography
Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC, Canada · Vancouver General Hospital, Vancouver, BC, Canada
Multimodal Ordinal Modeling of Alzheimer's Disease Severity Using Structural MRI and Clinical Data
Jun 10, 2026Boris-Stephan Rauchmann, Jonathan Laib, Buse Ercik +2Alzheimer's Disease Medical Image Classification
Department of Neuroradiology, LMU University Hospital, Ludwig Maximilian University of Munich, Munich, Germany · Department of Psychiatry and Psychotherapy, LMU University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
DiffoR: A Unified Continuous Generative Framework for Universal Ordinal Regression
May 29, 2026Hongxu Ma, Lin Wang, Chenghou Jin +6Ordinal Regression
Fudan University Shanghai, China · Kuaishou Technology Beijing, China · Shanghai University of Finance and Economics Shanghai, China +1
Learning Transferable Predictability Representations
May 28, 2026Diyali Goswami, Auroop R. GangulyDynamical Systems Ordinal Regression
Sustainability and Data Sciences Laboratory (SDS Lab), Northeastern University, Boston, MA, USA · AI4CaS: AI for Climate and Sustainability, Institute for Experiential AI, Northeastern University, Boston, MA, USA · Pacific Northwest National Laboratory (PNNL), Richland, WA, USA
From Kellgren-Lawrence to Calcium Pyrophosphate Crystal Deposition: A Soft-Labelling Framework for Knee Osteoarthritis Assessmen
May 27, 2026Francisco Bérchez-Moreno, Riccardo Rosati, Maria Chiara Fiorentino +6Label Distribution Learning Medical Image Classification
Departamento de Ciencia de la Computación e Inteligencia Artificial, Universidad de Córdoba, Córdoba, España · Department of Political Science, Communication, and International Relations, University of Macerata, Macerata, Italy · Department of Innovative Technologies in Medicine & Dentistry, Università degli Studi "G. D’Annunzio" Chieti - Pescara, Chieti, Italy +5
A novel ordinal multi-view aggregation scheme for oak defoliation
May 27, 2026Francisco Bérchez-Moreno, Ricardo Enrique Hernández-Lambraño, David Guijo-Rubio +4Ensemble Learning Multi-View Learning
Departamento de Ciencia de la Computación e Inteligencia Artificial, Universidad de Córdoba, Campus Universitario de Rabanales, Edificio Albert Einstein. Ctra. N-IV, Km. 396, Córdoba, 14071, Andalucía, Spain · Department of Forest Engineering, Laboratory of Dendrochronology, Silviculture and Global Change – DendrodatLab, Universidad de Córdoba, Campus Universitario de Rabanales. Ctra. N-IV, Km. 396, Córdoba, 14071, Andalucía, Spain · Departamento de Teoría de la Señal y Comunicaciones, Universidad de Alcala, Escuela Politécnica. Campus Universitario. Ctra. Madrid-Barcelona, Km. 33,600, Madrid, 28805, Madrid, Spain +1
An Effective Strategy for Modeling Score Ordinality and Non-uniform Intervals in Automated Speaking Assessment
Aug 27, 2025Tien-Hong Lo, Szu-Yu Chen, Yao-Ting Sung +1Speech Processing Ordinal Regression
Department of Computer Science and Information Engineering, National Taiwan Normal University · Department of Educational Psychology and Counseling, National Taiwan Normal University

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Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models

Yujie Chen, Antik Chakraborty, Anindya Bhadra

Department of Statistics Purdue University

Preference Learning Ordinal Regression Markov Random Fields Pairwise Preference Learning

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Multivariate ordinal data along with covariates are commonly collected in problems ranging from alignment of language models with human preferences, as well as in recommender systems. For example, data sets such as MovieLens contain several movies rated on a scale 1--5 by human users, along with their demographic information such as age or gender. Similarly, data sets such as HelpSteer collect human feedback on several attributes such as "helpfulness" or "verbosity" of LLM response on an ordinal scale, with covariates depending on the LLM prompt--response pairs. Unfortunately, the standard approaches for modeling these data (a) look at the attributes individually rather than jointly, and (b) often convert the data into pairwise or list-wise win--loss comparisons for fitting models such as Bradley--Terry and Plackett--Luce. Both of these lead to a coarsening of what is actually observed, which we address via a joint covariate-dependent consecutive ratio Markov random field model. We also show pairwise or listwise comparison models are obtained under restrictions of our joint model, and that joint modeling improves comparisons. We also develop a maximum likelihood inference procedure even in the presence of an intractable normalizer.

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