| SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning | | 2.42±0.13 | Semi-SST (ViT-Small) | 2025-05-31 |
| SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning | | 3.37±0.22 | Super-SST (ViT-Small) | 2025-05-31 |
| ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels | ✓ Link | 3.47 | SemiOccam | 2025-06-04 |
| Diff-SySC: An Approach Using Diffusion Models for Semi-Supervised Image Classification | | 3.65±0.10 | Diff-SySC | 2025-02-25 |
| Dash: Semi-Supervised Learning with Dynamic Thresholding | | 4.56±0.13 | Dash (RA) | 2021-09-01 |
| Debiased Learning from Naturally Imbalanced Pseudo-Labels | ✓ Link | 4.6 | DebiasPL (w/ FixMatch) | 2022-01-05 |
| Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning | ✓ Link | 4.74 | ShrinkMatch | 2023-08-13 |
| []() | | 4.77±0.09 | FixMatch+DM | |
| DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples | | 4.78±0.26 | DP-SSL | 2021-10-26 |
| FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling | ✓ Link | 4.8±0.06 | FlexMatch | 2021-10-15 |
| SimMatch: Semi-supervised Learning with Similarity Matching | ✓ Link | 4.84 | SimMatch | 2022-03-14 |
| SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning | | 4.87±0.26 | SelfMatch | 2021-01-16 |
| NP-Match: When Neural Processes meet Semi-Supervised Learning | ✓ Link | 4.87 | NP-Match | 2022-07-03 |
| FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning | ✓ Link | 4.88 | FreeMatch | 2022-05-15 |
| Contrastive Regularization for Semi-Supervised Learning | | 5.04 | FixMatch+CR | 2022-01-17 |
| FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence | ✓ Link | 5.07±0.33 | FixMatch (CTA) | 2020-01-21 |
| Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering | ✓ Link | 5.51±0.25 | Semi-MMDC | 2020-12-01 |
| DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision | ✓ Link | 5.56±0.42 | DoubleMatch | 2022-05-11 |
| ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring | ✓ Link | 6.27 | ReMixMatch | 2019-11-21 |
| RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms | ✓ Link | 7.6 | EnAET | 2019-12-18 |
| RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms | ✓ Link | 9.79 | RealMix | 2019-12-18 |
| MixMatch: A Holistic Approach to Semi-Supervised Learning | ✓ Link | 11.08 | MixMatch | 2019-05-06 |
| LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching | | 19.17 | LiDAM | 2020-10-13 |
| Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning | ✓ Link | 36.03 | VAT | 2017-04-13 |
| Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results | ✓ Link | 47.32 | MeanTeacher | 2017-03-06 |
| mixup: Beyond Empirical Risk Minimization | ✓ Link | 47.43 | MixUp | 2017-10-25 |
| Temporal Ensembling for Semi-Supervised Learning | ✓ Link | 53.12 | Ⅱ-Model | 2016-10-07 |