{"total":120,"rows":[{"id":"2106.04149","title":"To Smooth or Not? When Label Smoothing Meets Noisy Labels","created":"2021-06-08","cited_by_count":70,"area":null},{"id":"2110.12911","title":"Instance-Dependent Partial Label Learning","created":"2021-10-25","cited_by_count":49,"area":null},{"id":"2103.02140","title":"PML: Progressive Margin Loss for Long-tailed Age Classification","created":"2021-03-03","cited_by_count":32,"area":null},{"id":"2209.10448","title":"Uncertainty-aware Label Distribution Learning for Facial Expression Recognition","created":"2022-09-21","cited_by_count":30,"area":null},{"id":"2204.00309","title":"Unimodal-Concentrated Loss: Fully Adaptive Label Distribution Learning for Ordinal Regression","created":"2022-04-01","cited_by_count":23,"area":null},{"id":"2404.11023","title":"Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions","created":"2024-04-17","cited_by_count":22,"area":null},{"id":"2106.11145","title":"FP-Age: Leveraging Face Parsing Attention for Facial Age Estimation in the Wild","created":"2021-06-21","cited_by_count":20,"area":null},{"id":"2308.01742","title":"Exploiting Multi-Label Correlation in Label Distribution Learning","created":"2023-08-03","cited_by_count":20,"area":null},{"id":"2111.11029","title":"Auto-Encoding Score Distribution Regression for Action Quality Assessment","created":"2021-11-22","cited_by_count":18,"area":null},{"id":"2106.12450","title":"A Circular-Structured Representation for Visual Emotion Distribution Learning","created":"2021-06-23","cited_by_count":17,"area":null},{"id":"2112.10167","title":"Improving Face-Based Age Estimation with Attention-Based Dynamic Patch Fusion","created":"2021-12-19","cited_by_count":13,"area":null},{"id":"2212.07328","title":"Modeling Multimodal Aleatoric Uncertainty in Segmentation with Mixture of Stochastic Experts","created":"2022-12-14","cited_by_count":13,"area":null},{"id":"2302.13000","title":"Inaccurate Label Distribution Learning","created":"2023-02-25","cited_by_count":10,"area":null},{"id":"2205.13358","title":"Transfer and Share: Semi-Supervised Learning from Long-Tailed Data","created":"2022-05-26","cited_by_count":9,"area":null},{"id":"2104.13718","title":"Graph Decoupling Attention Markov Networks for Semi-supervised Graph Node Classification","created":"2021-04-28","cited_by_count":8,"area":null},{"id":"2206.06623","title":"ULTRA: Uncertainty-aware Label Distribution Learning for Breast Tumor Cellularity Assessment","created":"2022-06-14","cited_by_count":7,"area":null},{"id":"2210.03968","title":"A Survey on Extreme Multi-label Learning","created":"2022-10-08","cited_by_count":7,"area":null},{"id":"2307.10189","title":"Subjective Crowd Disagreements for Subjective Data: Uncovering Meaningful CrowdOpinion with Population-level Learning","created":"2023-07-07","cited_by_count":7,"area":null},{"id":"2209.13824","title":"Label Distribution Learning via Implicit Distribution Representation","created":"2022-09-28","cited_by_count":6,"area":null},{"id":"2409.16071","title":"Learning with Confidence: Training Better Classifiers from Soft Labels","created":"2024-09-24","cited_by_count":6,"area":null},{"id":"2204.05903","title":"Label Distribution Learning for Generalizable Multi-source Person Re-identification","created":"2022-04-12","cited_by_count":5,"area":null},{"id":"2207.11875","title":"Seeking Subjectivity in Visual Emotion Distribution Learning","created":"2022-07-25","cited_by_count":5,"area":null},{"id":"2308.07779","title":"Do We Fully Understand Students' Knowledge States? Identifying and Mitigating Answer Bias in Knowledge Tracing","created":"2023-08-15","cited_by_count":5,"area":null},{"id":"2312.00351","title":"Manipulating the Label Space for In-Context Classification","created":"2023-12-01","cited_by_count":5,"area":null},{"id":"2502.01170","title":"Label Distribution Learning with Biased Annotations by Learning Multi-Label Representation","created":"2025-02-03","cited_by_count":5,"area":null},{"id":"2106.11482","title":"Wallpaper Texture Generation and Style Transfer Based on Multi-label Semantics","created":"2021-06-22","cited_by_count":4,"area":null},{"id":"2201.07423","title":"Many Ways to Be Lonely: Fine-Grained Characterization of Loneliness and Its Potential Changes in COVID-19","created":"2022-01-19","cited_by_count":4,"area":null},{"id":"2203.17156","title":"Adaptive Mean-Residue Loss for Robust Facial Age Estimation","created":"2022-03-31","cited_by_count":4,"area":null},{"id":"2303.06836","title":"Label Information Bottleneck for Label Enhancement","created":"2023-03-13","cited_by_count":4,"area":null},{"id":"2403.00268","title":"Improving Acne Image Grading with Label Distribution Smoothing","created":"2024-03-01","cited_by_count":4,"area":null},{"id":"2102.01934","title":"Noise-robust classification with hypergraph neural network","created":"2021-02-03","cited_by_count":3,"area":null},{"id":"2106.02051","title":"The Earth Mover's Pinball Loss: Quantiles for Histogram-Valued Regression","created":"2021-06-03","cited_by_count":3,"area":null},{"id":"2106.10600","title":"Improving Label Quality by Jointly Modeling Items and Annotators","created":"2021-06-20","cited_by_count":3,"area":null},{"id":"2107.03250","title":"Understanding Intrinsic Robustness Using Label Uncertainty","created":"2021-07-07","cited_by_count":3,"area":null},{"id":"2209.02055","title":"Full Kullback-Leibler-Divergence Loss for Hyperparameter-free Label Distribution Learning","created":"2022-09-05","cited_by_count":3,"area":null},{"id":"2211.13196","title":"SeedBERT: Recovering Annotator Rating Distributions from an Aggregated Label","created":"2022-11-23","cited_by_count":3,"area":null},{"id":"2303.06847","title":"Label Distribution Learning from Logical Label","created":"2023-03-13","cited_by_count":3,"area":null},{"id":"2312.06343","title":"RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations","created":"2023-12-11","cited_by_count":3,"area":null},{"id":"2404.04313","title":"JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer","created":"2024-04-05","cited_by_count":3,"area":null},{"id":"2101.09858","title":"Weakly Supervised Learning for Facial Affective Behavior Analysis : A Review","created":"2021-01-25","cited_by_count":2,"area":null},{"id":"2102.06164","title":"Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels","created":"2021-02-11","cited_by_count":2,"area":null},{"id":"2102.13269","title":"Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification","created":"2021-02-26","cited_by_count":2,"area":null},{"id":"2103.00899","title":"Computationally Efficient Wasserstein Loss for Structured Labels","created":"2021-03-01","cited_by_count":2,"area":null},{"id":"2210.09524","title":"SVLDL: Improved Speaker Age Estimation Using Selective Variance Label Distribution Learning","created":"2022-10-18","cited_by_count":2,"area":null},{"id":"2212.01742","title":"Lightweight Facial Attractiveness Prediction Using Dual Label Distribution","created":"2022-12-04","cited_by_count":2,"area":null},{"id":"2303.16464","title":"Lipschitzness Effect of a Loss Function on Generalization Performance of Deep Neural Networks Trained by Adam and AdamW Optimizers","created":"2023-03-29","cited_by_count":2,"area":null},{"id":"2308.03000","title":"StyleEDL: Style-Guided High-order Attention Network for Image Emotion Distribution Learning","created":"2023-08-06","cited_by_count":2,"area":null},{"id":"2309.04318","title":"Generating the Ground Truth: Synthetic Data for Soft Label and Label Noise Research","created":"2023-09-08","cited_by_count":2,"area":null},{"id":"2508.08163","title":"LPI-RIT at LeWiDi-2025: Improving Distributional Predictions via Metadata and Loss Reweighting with DisCo","created":"2025-08-11","cited_by_count":2,"area":null},{"id":"2510.16601","title":"Uncertain Knowledge Graph Completion via Semi-Supervised Confidence Distribution Learning","created":"2025-10-18","cited_by_count":2,"area":null},{"id":"2511.14117","title":"Distributions In, Distributions Out: The Case for Soft-Label Training","created":"2025-11-18","cited_by_count":2,"area":null},{"id":"2606.22725","title":"Interpretable Uncertainty Routing Separating Emotion Ambiguity from Distribution Shift in Facial Expression Recognition","created":"2026-06-21","cited_by_count":2,"area":null},{"id":"2205.15265","title":"Going Beyond One-Hot Encoding in Classification: Can Human Uncertainty Improve Model Performance?","created":"2022-05-30","cited_by_count":1,"area":null},{"id":"2208.01161","title":"Pose Uncertainty Aware Movement Synchrony Estimation via Spatial-Temporal Graph Transformer","created":"2022-08-01","cited_by_count":1,"area":null},{"id":"2210.08184","title":"Label distribution learning via label correlation grid","created":"2022-10-15","cited_by_count":1,"area":null},{"id":"2308.07047","title":"No Regularization is Needed: An Efficient and Effective Model for Incomplete Label Distribution Learning","created":"2023-08-14","cited_by_count":1,"area":null},{"id":"2311.08874","title":"Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty","created":"2023-11-15","cited_by_count":1,"area":null},{"id":"2405.16474","title":"Inaccurate Label Distribution Learning with Dependency Noise","created":"2024-05-26","cited_by_count":1,"area":null},{"id":"2505.05834","title":"Dual-level Fuzzy Learning with Patch Guidance for Image Ordinal Regression","created":"2025-05-09","cited_by_count":1,"area":null},{"id":"2505.15140","title":"EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression","created":"2025-05-21","cited_by_count":1,"area":null},{"id":"2505.21576","title":"Concentration Distribution Learning from Label Distributions","created":"2025-05-27","cited_by_count":1,"area":null},{"id":"2506.13445","title":"Overcoming Occlusions in the Wild: A Multi-Task Age Head Approach to Age Estimation","created":"2025-06-16","cited_by_count":1,"area":null},{"id":"2507.06821","title":"HeLo: Heterogeneous Multi-Modal Fusion with Label Correlation for Emotion Distribution Learning","created":"2025-07-09","cited_by_count":1,"area":null},{"id":"2511.00129","title":"Data-Augmented Deep Learning for Downhole Depth Sensing and Validation","created":"2025-10-31","cited_by_count":1,"area":null},{"id":"2602.20530","title":"Memory-guided Prototypical Co-occurrence Learning for Mixed Emotion Recognition","created":"2026-02-24","cited_by_count":1,"area":null},{"id":"2605.04827","title":"Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2101.11422","title":"Cisco at AAAI-CAD21 shared task: Predicting Emphasis in Presentation Slides using Contextualized Embeddings","created":"2021-01-10","cited_by_count":0,"area":null},{"id":"2103.15107","title":"Hierarchical Relationship Alignment Metric Learning","created":"2021-03-28","cited_by_count":0,"area":null},{"id":"2106.09393","title":"using multiple losses for accurate facial age estimation","created":"2021-06-17","cited_by_count":0,"area":null},{"id":"2108.12750","title":"Sentence Structure and Word Relationship Modeling for Emphasis Selection","created":"2021-08-29","cited_by_count":0,"area":null},{"id":"2110.06630","title":"Fuzzy Overclustering: Semi-Supervised Classification of Fuzzy Labels with Overclustering and Inverse Cross-Entropy","created":"2021-10-13","cited_by_count":0,"area":null},{"id":"2204.03845","title":"Decompositional Generation Process for Instance-Dependent Partial Label Learning","created":"2022-04-08","cited_by_count":0,"area":null},{"id":"2210.13852","title":"TabMixer: Excavating Label Distribution Learning with Small-scale Features","created":"2022-10-25","cited_by_count":0,"area":null},{"id":"2303.11698","title":"Data Augmentation For Label Enhancement","created":"2023-03-21","cited_by_count":0,"area":null},{"id":"2304.10705","title":"Graph based Label Enhancement for Multi-instance Multi-label learning","created":"2023-04-21","cited_by_count":0,"area":null},{"id":"2305.09500","title":"Contrastive Label Enhancement","created":"2023-05-16","cited_by_count":0,"area":null},{"id":"2311.03076","title":"SugarViT -- Multi-objective Regression of UAV Images with Vision Transformers and Deep Label Distribution Learning Demonstrated on Disease Severity Prediction in Sugar Beet","created":"2023-11-06","cited_by_count":0,"area":null},{"id":"2311.16556","title":"Scalable Label Distribution Learning for Multi-Label Classification","created":"2023-11-28","cited_by_count":0,"area":null},{"id":"2403.17914","title":"Hierarchical Multi-label Classification for Fine-level Event Extraction from Aviation Accident Reports","created":"2024-03-26","cited_by_count":0,"area":null},{"id":"2404.15714","title":"Ada-DF: An Adaptive Label Distribution Fusion Network For Facial Expression Recognition","created":"2024-04-24","cited_by_count":0,"area":null},{"id":"2410.13579","title":"Towards Better Performance in Incomplete LDL: Addressing Data Imbalance","created":"2024-10-17","cited_by_count":0,"area":null},{"id":"2411.06160","title":"Expansion Quantization Network: An Efficient Micro-emotion Annotation and Detection Framework","created":"2024-11-09","cited_by_count":0,"area":null},{"id":"2411.13097","title":"Incremental Label Distribution Learning with Scalable Graph Convolutional Networks","created":"2024-11-20","cited_by_count":0,"area":null},{"id":"2412.07324","title":"Label Distribution Learning using the Squared Neural Family on the Probability Simplex","created":"2024-12-10","cited_by_count":0,"area":null},{"id":"2503.04869","title":"Label Distribution Learning-Enhanced Dual-KNN for Text Classification","created":"2025-03-06","cited_by_count":0,"area":null},{"id":"2504.01508","title":"UAKNN: Label Distribution Learning via Uncertainty-Aware KNN","created":"2025-04-02","cited_by_count":0,"area":null},{"id":"2504.19374","title":"From Distance to Direction: Structure-aware Label-specific Feature Fusion for Label Distribution Learning","created":"2025-04-27","cited_by_count":0,"area":null},{"id":"2505.21180","title":"Latent label distribution grid representation for modeling uncertainty","created":"2025-05-27","cited_by_count":0,"area":null},{"id":"2508.21772","title":"UniMLR: Modeling Implicit Class Significance for Multi-Label Ranking","created":"2025-08-29","cited_by_count":0,"area":null},{"id":"2509.02351","title":"Ordinal Adaptive Correction: A Data-Centric Approach to Ordinal Image Classification with Noisy Labels","created":"2025-09-02","cited_by_count":0,"area":null},{"id":"2509.09524","title":"DeMeVa at LeWiDi-2025: Modeling Perspectives with In-Context Learning and Label Distribution Learning","created":"2025-09-11","cited_by_count":0,"area":null},{"id":"2510.13917","title":"Multi-View Semi-Supervised Label Distribution Learning with Local Structure Complementarity","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2511.07165","title":"Fuzzy Label: From Concept to Its Application in Label Learning","created":"2025-11-10","cited_by_count":0,"area":null},{"id":"2511.09702","title":"Classifying Phonotrauma Severity from Vocal Fold Images with Soft Ordinal Regression","created":"2025-11-12","cited_by_count":0,"area":null},{"id":"2511.12494","title":"Towards Better IncomLDL: We Are Unaware of Hidden Labels in Advance","created":"2025-11-16","cited_by_count":0,"area":null},{"id":"2511.20106","title":"EM2LDL: A Multilingual Speech Corpus for Mixed Emotion Recognition through Label Distribution Learning","created":"2025-11-25","cited_by_count":0,"area":null},{"id":"2512.08371","title":"A Multivariate Bernoulli-Based Sampling Method for Multi-Label Data with Application to Meta-Research","created":"2025-12-09","cited_by_count":0,"area":null},{"id":"2602.00407","title":"Fed-Listing: Federated Label Distribution Inference in Graph Neural Networks","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2603.23650","title":"Foundation Model Embeddings Meet Blended Emotions: A Multimodal Fusion Approach for the BLEMORE Challenge","created":"2026-03-24","cited_by_count":0,"area":null},{"id":"2604.08425","title":"Learning Who Disagrees: Demographic Importance Weighting for Modeling Annotator Distributions with DiADEM","created":"2026-04-09","cited_by_count":0,"area":null}],"next_cursor":"100"}