Overview

Pseudo-labeling studies how to use model-generated labels to learn from unlabeled examples, making it useful when human annotation is scarce or expensive. Common approaches include teacher–student self-training, confidence thresholding, consistency training, and iterative refinement, with applications spanning image segmentation, speech recognition, domain adaptation, and graph learning. Recent methods add calibration, uncertainty estimates, foundation-model cues, or temporal and multimodal agreement to decide which predictions to trust. The central tension is that more pseudo-labels increase coverage but can also amplify errors and confirmation bias, so gains depend on label quality, distribution shift, and the task.

Latest papers

CardsList

159 papers16 papers in the last four weeks, down 36% on the four weeks before. 0.1% of all new papers.

  1. RABC-Net: Reliability-Aware Annotation-Free Skin Lesion Segmentation for Low-Resource Dermoscopy

    Apr 7, 2026Yujie Yao, Yuhaohang He, Junjie Huang +6Skin Lesion SegmentationBoundary-Aware Segmentation

  2. EventHub: Data Factory for Generalizable Event-Based Stereo Networks without Active Sensors

    Apr 2, 2026Luca Bartolomei, Fabio Tosi, Matteo Poggi +2Event-Based VisionStereo Matching

  3. Foundation Model-guided Iteratively Prompting and Pseudo-Labeling for Partially Labeled Medical Image Segmentation

    Apr 1, 2026Qiaochu Zhao, Wei Wei, David Horowitz +2Medical Image SegmentationPseudo-Labeling

  4. Make It Up: Fake Images, Real Gains in Generalized Few-shot Semantic Segmentation

    Mar 28, 2026Guohuan Xie, Xin He, Dingying Fan +3Few-Shot Semantic SegmentationSemantic Segmentation

  5. Denoise and Align: Towards Source-Free UDA for Robust Panoramic Semantic Segmentation

    Mar 26, 2026Yaowen Chang, Zhen Cao, Xu Zheng +2Semantic SegmentationSource-Free Domain Adaptation

  6. Pseudo Label NCF for Sparse OHC Recommendation: Dual Representation Learning and the Separability Accuracy Trade off

    Mar 25, 2026Pronob Kumar Barman, Tera L. Reynolds, James FouldsCollaborative FilteringCold-Start Recommendation

  7. BCMDA: Bidirectional Correlation Maps Domain Adaptation for Mixed Domain Semi-Supervised Medical Image Segmentation

    Mar 25, 2026Bentao Song, Jun Huang, Qingfeng WangSemi-Supervised Medical Image SegmentationUnsupervised Domain Adaptation

  8. HACMatch Semi-Supervised Rotation Regression with Hardness-Aware Curriculum Pseudo Labeling

    Mar 23, 2026Mei Li, Huayi Zhou, Suizhi Huang +3Object Pose EstimationSemi-Supervised Learning

  9. CTFS : Collaborative Teacher Framework for Forward-Looking Sonar Image Semantic Segmentation with Extremely Limited Labels

    Mar 22, 2026Ping Guo, Chengzhou Li, Guanchen Meng +6Image SegmentationSemantic Segmentation

  10. What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time

    Mar 20, 2026Dong Yan, Jian Liang, Yanbo Wang +3RL for Language Model ReasoningTest-Time RL

  11. Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs

    Mar 19, 2026Nathan Weill, Kaizheng WangUnsupervised Domain AdaptationCovariate Shift

  12. When the City Teaches the Car: Label-Free 3D Perception from Infrastructure

    Mar 17, 2026Zhen Xu, Jinsu Yoo, Cristian Bautista +7Autonomous Driving3D Object Detection

  13. Real-World Point Tracking with Verifier-Guided Pseudo-Labeling

    Mar 12, 2026Görkay Aydemir, Fatma Güney, Weidi XiePoint TrackingPseudo-Labeling

  14. EReCu: Pseudo-label Evolution Fusion and Refinement with Multi-Cue Learning for Unsupervised Camouflage Detection

    Mar 12, 2026Shuo Jiang, Gaojia Zhang, Min Tan +2Pseudo-LabelingUnsupervised Camouflaged Object Detection

  15. GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

    Mar 11, 2026Ruiyao Xu, Kaize DingText-Attributed Graph LearningLLMs for Graph Learning

  16. Weakly Supervised Teacher-Student Framework with Progressive Pseudo-mask Refinement for Gland Segmentation

    Mar 9, 2026Hikmat Khan, Wei Chen, Muhammad Khalid Khan NiaziHistopathology Image SegmentationMedical Image Segmentation

  17. DDS-UDA: Dual-Domain Synergy for Unsupervised Domain Adaptation in Joint Segmentation of Optic Disc and Optic Cup

    Mar 7, 2026Yusong Xiao, Yuxuan Wu, Li Xiao +3Medical Image SegmentationUnsupervised Domain Adaptation

  18. Point-Supervised Skeleton-Based Human Action Segmentation

    Mar 6, 2026Hongsong Wang, Yiqin Shen, Pengbo Yan +2Temporal Action SegmentationPseudo-Labeling

  19. A Semi-Supervised Framework for Breast Ultrasound Segmentation with Training-Free Pseudo-Label Generation and Label Refinement

    Mar 6, 2026Ruili Li, Jiayi Ding, Ruiyu Li +7Ultrasound Image SegmentationSemi-Supervised Medical Image Segmentation

  20. Semi-Supervised Few-Shot Adaptation of Vision-Language Models

    Mar 3, 2026Julio Silva-Rodríguez, Ender KonukogluVLM AdaptationFew-Shot Image Classification

  21. Unsupervised Semantic Segmentation in Synchrotron Computed Tomography with Self-Correcting Pseudo Labels

    Feb 27, 2026Austin Yunker, Peter Kenesei, Hemant Sharma +3Unsupervised Image Segmentation3D Semantic Segmentation

  22. PSQE: A Theoretical-Practical Approach to Pseudo Seed Quality Enhancement for Unsupervised Multimodal Entity Alignment

    Feb 26, 2026Yunpeng Hong, Chenyang Bu, Jie Zhang +3Cross-Modal AlignmentPseudo-Labeling

  23. Unified Unsupervised and Sparsely-Supervised 3D Object Detection by Semantic Pseudo-Labeling and Prototype Learning

    Feb 25, 2026Yushen He, Lei Zhao, Weidong Chen3D Object DetectionPseudo-Labeling

  24. Generative Pseudo-Labeling for Pre-Ranking with LLMs

    Feb 24, 2026Junyu Bi, Xinting Niu, Daixuan Cheng +4Pseudo-LabelingRecommender Systems

  25. DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation

    Feb 24, 2026Wangkai Li, Rui Sun, Zhaoyang Li +2Model CalibrationSemantic Segmentation

  26. Gradient based Severity Labeling for Biomarker Classification in OCT

    Feb 23, 2026Kiran Kokilepersaud, Mohit Prabhushankar, Ghassan AlRegib +2ClassificationPseudo-Labeling

  27. Enhancing Automatic Chord Recognition via Pseudo-Labeling and Knowledge Distillation

    Feb 23, 2026Nghia Phan, Rong Jin, Gang Liu +1Pseudo-LabelingMusic Information Retrieval

  28. Pay Attention to CTC: Fast and Robust Pseudo-Labelling for Unified Speech Recognition

    Feb 22, 2026Alexandros Haliassos, Rodrigo Mira, Stavros PetridisConnectionist Temporal ClassificationAutomatic Speech Recognition