{"total":82,"rows":[{"id":"2110.08263","title":"FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling","created":"2021-10-15","cited_by_count":540,"area":null},{"id":"2101.10382","title":"Curriculum Learning: A Survey","created":"2021-01-25","cited_by_count":259,"area":null},{"id":"2205.07246","title":"FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning","created":"2022-05-15","cited_by_count":232,"area":null},{"id":"2102.03526","title":"Open-World Semi-Supervised Learning","created":"2021-02-06","cited_by_count":165,"area":null},{"id":"2211.11727","title":"Parametric Classification for Generalized Category Discovery: A Baseline Study","created":"2022-11-21","cited_by_count":113,"area":null},{"id":"2208.07204","title":"USB: A Unified Semi-supervised Learning Benchmark for Classification","created":"2022-08-12","cited_by_count":95,"area":null},{"id":"2305.06144","title":"Learning Semi-supervised Gaussian Mixture Models for Generalized Category Discovery","created":"2023-05-10","cited_by_count":72,"area":null},{"id":"2103.00236","title":"Uncertainty-Aware Unsupervised Domain Adaptation in Object Detection","created":"2021-02-27","cited_by_count":60,"area":null},{"id":"2208.11296","title":"Semi-Supervised and Unsupervised Deep Visual Learning: A Survey","created":"2022-08-24","cited_by_count":52,"area":null},{"id":"2105.14148","title":"OpenMatch: Open-set Consistency Regularization for Semi-supervised Learning with Outliers","created":"2021-05-28","cited_by_count":43,"area":null},{"id":"2207.03162","title":"Harnessing Out-Of-Distribution Examples via Augmenting Content and Style","created":"2022-07-07","cited_by_count":43,"area":null},{"id":"2108.05617","title":"Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning","created":"2021-08-12","cited_by_count":40,"area":null},{"id":"2407.21794","title":"Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey","created":"2024-07-31","cited_by_count":36,"area":"mllm"},{"id":"2208.02764","title":"OpenCon: Open-world Contrastive Learning","created":"2022-08-04","cited_by_count":33,"area":null},{"id":"2308.06714","title":"Learning on Graphs with Out-of-Distribution Nodes","created":"2023-08-13","cited_by_count":29,"area":null},{"id":"2304.14310","title":"Incremental Generalized Category Discovery","created":"2023-04-27","cited_by_count":25,"area":null},{"id":"2201.06247","title":"Contrastive Regularization for Semi-Supervised Learning","created":"2022-01-17","cited_by_count":24,"area":null},{"id":"2203.05114","title":"OpenTAL: Towards Open Set Temporal Action Localization","created":"2022-03-10","cited_by_count":23,"area":null},{"id":"2308.13168","title":"IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization","created":"2023-08-25","cited_by_count":23,"area":null},{"id":"2404.11998","title":"Curriculum Point Prompting for Weakly-Supervised Referring Image Segmentation","created":"2024-04-18","cited_by_count":23,"area":null},{"id":"2311.03524","title":"A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning","created":"2023-11-06","cited_by_count":22,"area":null},{"id":"2311.01002","title":"Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy","created":"2023-11-02","cited_by_count":20,"area":null},{"id":"2405.06979","title":"Robust Semi-supervised Learning by Wisely Leveraging Open-set Data","created":"2024-05-11","cited_by_count":20,"area":null},{"id":"2208.13722","title":"Open-Set Semi-Supervised Object Detection","created":"2022-08-29","cited_by_count":17,"area":null},{"id":"2305.13095","title":"Open-world Semi-supervised Novel Class Discovery","created":"2023-05-22","cited_by_count":15,"area":null},{"id":"2504.04804","title":"DebGCD: Debiased Learning with Distribution Guidance for Generalized Category Discovery","created":"2025-04-07","cited_by_count":15,"area":null},{"id":"2407.19001","title":"Effective Prompt Pool Learning for Continual Category Discovery","created":"2024-07-26","cited_by_count":14,"area":null},{"id":"2106.00417","title":"Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners","created":"2021-06-01","cited_by_count":13,"area":null},{"id":"2111.11288","title":"SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise","created":"2021-11-22","cited_by_count":13,"area":null},{"id":"2303.07269","title":"InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning","created":"2023-03-13","cited_by_count":12,"area":null},{"id":"2303.11101","title":"Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning","created":"2023-03-20","cited_by_count":12,"area":null},{"id":"2310.01376","title":"Towards Distribution-Agnostic Generalized Category Discovery","created":"2023-10-02","cited_by_count":12,"area":null},{"id":"2208.11870","title":"Fix-A-Step: Semi-supervised Learning from Uncurated Unlabeled Data","created":"2022-08-25","cited_by_count":11,"area":null},{"id":"2301.08390","title":"Open-Set Likelihood Maximization for Few-Shot Learning","created":"2023-01-20","cited_by_count":10,"area":null},{"id":"2302.14483","title":"RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data","created":"2023-02-28","cited_by_count":10,"area":null},{"id":"2205.06701","title":"Knowledge Distillation Meets Open-Set Semi-Supervised Learning","created":"2022-05-13","cited_by_count":9,"area":"distill"},{"id":"2311.10572","title":"SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning","created":"2023-11-17","cited_by_count":9,"area":null},{"id":"2203.00190","title":"Semi-supervised Deep Learning for Image Classification with Distribution Mismatch: A Survey","created":"2022-03-01","cited_by_count":8,"area":null},{"id":"2412.18256","title":"Robust Semi-Supervised Learning in Open Environments","created":"2024-12-24","cited_by_count":8,"area":null},{"id":"2110.15231","title":"Exploring Covariate and Concept Shift for Detection and Calibration of Out-of-Distribution Data","created":"2021-10-28","cited_by_count":7,"area":null},{"id":"2305.18158","title":"Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning","created":"2023-05-29","cited_by_count":7,"area":null},{"id":"2101.08237","title":"An Empirical Study and Analysis on Open-Set Semi-Supervised Learning","created":"2021-01-19","cited_by_count":6,"area":null},{"id":"2301.10127","title":"Improving Open-Set Semi-Supervised Learning with Self-Supervision","created":"2023-01-24","cited_by_count":6,"area":null},{"id":"2407.19752","title":"Contextuality Helps Representation Learning for Generalized Category Discovery","created":"2024-07-29","cited_by_count":6,"area":null},{"id":"2207.09280","title":"Exploiting Inter-Sample Affinity for Knowability-Aware Universal Domain Adaptation","created":"2022-07-19","cited_by_count":5,"area":null},{"id":"2204.14249","title":"OSSGAN: Open-Set Semi-Supervised Image Generation","created":"2022-04-29","cited_by_count":4,"area":null},{"id":"2301.06010","title":"On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning","created":"2023-01-15","cited_by_count":4,"area":null},{"id":"2303.15485","title":"Transfer-Once-For-All: AI Model Optimization for Edge","created":"2023-03-27","cited_by_count":4,"area":null},{"id":"2310.05498","title":"Semi-Supervised Object Detection with Uncurated Unlabeled Data for Remote Sensing Images","created":"2023-10-09","cited_by_count":4,"area":null},{"id":"2202.05975","title":"Robust Deep Semi-Supervised Learning: A Brief Introduction","created":"2022-02-12","cited_by_count":3,"area":null},{"id":"2205.01006","title":"Open-Set Semi-Supervised Learning for 3D Point Cloud Understanding","created":"2022-05-02","cited_by_count":3,"area":null},{"id":"2303.12091","title":"Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning","created":"2023-03-21","cited_by_count":3,"area":null},{"id":"2407.11735","title":"ProSub: Probabilistic Open-Set Semi-Supervised Learning with Subspace-Based Out-of-Distribution Detection","created":"2024-07-16","cited_by_count":3,"area":null},{"id":"2409.17512","title":"SCOMatch: Alleviating Overtrusting in Open-set Semi-supervised Learning","created":"2024-09-26","cited_by_count":3,"area":null},{"id":"2411.01833","title":"OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning","created":"2024-11-04","cited_by_count":3,"area":null},{"id":"2503.00884","title":"Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model","created":"2025-03-02","cited_by_count":3,"area":null},{"id":"2206.09236","title":"Model-Agnostic Few-Shot Open-Set Recognition","created":"2022-06-18","cited_by_count":2,"area":null},{"id":"2209.14205","title":"Prompt-driven efficient Open-set Semi-supervised Learning","created":"2022-09-28","cited_by_count":2,"area":null},{"id":"2210.06833","title":"Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes","created":"2022-10-13","cited_by_count":2,"area":null},{"id":"2306.01222","title":"Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2306.17699","title":"Exploration and Exploitation of Unlabeled Data for Open-Set Semi-Supervised Learning","created":"2023-06-30","cited_by_count":2,"area":null},{"id":"2307.03741","title":"Training Ensembles with Inliers and Outliers for Semi-supervised Active Learning","created":"2023-07-07","cited_by_count":2,"area":null},{"id":"2505.06948","title":"Unsupervised Learning for Class Distribution Mismatch","created":"2025-05-11","cited_by_count":2,"area":null},{"id":"2509.22769","title":"PartCo: Part-Level Correspondence Priors Enhance Category Discovery","created":"2025-09-26","cited_by_count":2,"area":null},{"id":"2303.09930","title":"Robust Semi-Supervised Learning for Histopathology Images through Self-Supervision Guided Out-of-Distribution Scoring","created":"2023-03-17","cited_by_count":1,"area":null},{"id":"2303.11702","title":"On the link between generative semi-supervised learning and generative open-set recognition","created":"2023-03-21","cited_by_count":1,"area":null},{"id":"2308.14119","title":"Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario","created":"2023-08-27","cited_by_count":1,"area":null},{"id":"2503.00286","title":"A Unified Framework for Heterogeneous Semi-supervised Learning","created":"2025-03-01","cited_by_count":1,"area":null},{"id":"2505.24443","title":"Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers","created":"2025-05-30","cited_by_count":1,"area":null},{"id":"2506.12515","title":"Generalized Category Discovery under the Long-Tailed Distribution","created":"2025-06-14","cited_by_count":1,"area":null},{"id":"2209.09616","title":"Provably Uncertainty-Guided Universal Domain Adaptation","created":"2022-09-19","cited_by_count":0,"area":null},{"id":"2211.02142","title":"Improving Semi-supervised Deep Learning by using Automatic Thresholding to Deal with Out of Distribution Data for COVID-19 Detection using Chest X-ray Images","created":"2022-11-03","cited_by_count":0,"area":null},{"id":"2301.04506","title":"A Distinct Unsupervised Reference Model From The Environment Helps Continual Learning","created":"2023-01-11","cited_by_count":0,"area":null},{"id":"2305.13802","title":"Online Open-set Semi-supervised Object Detection with Dual Competing Head","created":"2023-05-23","cited_by_count":0,"area":null},{"id":"2307.08319","title":"Soft Curriculum for Learning Conditional GANs with Noisy-Labeled and Uncurated Unlabeled Data","created":"2023-07-17","cited_by_count":0,"area":null},{"id":"2405.16093","title":"Diverse Teacher-Students for Deep Safe Semi-Supervised Learning under Class Mismatch","created":"2024-05-25","cited_by_count":0,"area":"distill"},{"id":"2408.01872","title":"Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples","created":"2024-08-03","cited_by_count":0,"area":null},{"id":"2412.13036","title":"Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2504.12569","title":"Let the Void Be Void: Robust Open-Set Semi-Supervised Learning via Selective Non-Alignment","created":"2025-04-17","cited_by_count":0,"area":null},{"id":"2508.00922","title":"CaliMatch: Adaptive Calibration for Improving Safe Semi-supervised Learning","created":"2025-07-30","cited_by_count":0,"area":null},{"id":"2510.25926","title":"Active Learning with Task-Driven Representations for Messy Pools","created":"2025-10-29","cited_by_count":0,"area":null},{"id":"2606.26973","title":"Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning","created":"2026-06-25","cited_by_count":0,"area":null}],"next_cursor":null}