| Learning to Clean: Reinforcement Learning for Noisy Label Correction | | 90.2 | | | RLNLC | 2025-11-25 |
| Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer | ✓ Link | 89.0 | DeiT-S | NO | Jigsaw-ViT | 2022-07-25 |
| SURE: SUrvey REcipes for building reliable and robust deep networks | ✓ Link | 89.0 | Vgg19-BN | NO | SURE | 2024-03-01 |
| CLIPCleaner: Cleaning Noisy Labels with CLIP | ✓ Link | 88.85 | Vgg19-BN | NO | CLIPCleaner | 2024-08-19 |
| PSSCL: A progressive sample selection framework with contrastive loss designed for noisy labels | ✓ Link | 88.74 | Vgg19-BN | NO | PSSCL | 2024-12-18 |
| SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise | ✓ Link | 88.5 | Vgg19-BN | NO | SSR | 2021-11-22 |
| Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels | ✓ Link | 88.5 | Vgg19-BN | NO | BtR | 2022-10-17 |
| Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels | ✓ Link | 86.8 | VGG19-BN | NO | SPR | 2022-03-15 |
| Dynamic Loss For Robust Learning | ✓ Link | 86.5 | Vgg19-BN | NO | Dynamic Loss | 2022-11-22 |
| Partial Label Supervision for Agnostic Generative Noisy Label Learning | ✓ Link | 85.9 | Vgg-19-BN | NO | GNL | 2023-08-02 |
| Cross-to-merge training with class balance strategy for learning with noisy labels | ✓ Link | 85.9 | Vgg-19-BN | NO | C2MT | 2024-04-01 |
| Instance-Dependent Noisy Label Learning via Graphical Modelling | ✓ Link | 84.7 | ConvNeXt | NO | InstanceGM with ConvNeXt | 2022-09-02 |
| Instance-Dependent Noisy Label Learning via Graphical Modelling | ✓ Link | 84.6 | Vgg19-BN | NO | InstanceGM | 2022-09-02 |
| Compressing Features for Learning with Noisy Labels | ✓ Link | 84.1 | Vgg19-BN | NO | Nested+Co-teaching (NCT) | 2022-06-27 |
| Learning with Feature-Dependent Label Noise: A Progressive Approach | ✓ Link | 83.4 | Vgg19-BN | NO | PLC | 2021-03-13 |
| Instance-Dependent Noisy Label Learning via Graphical Modelling | ✓ Link | 82.3 | ResNet | NO | InstanceGM with ResNet | 2022-09-02 |
| SELFIE: Refurbishing Unclean Samples for Robust Deep Learning | ✓ Link | 81.8 | Vgg19-BN | NO | SELFIE | 2019-06-15 |
| Boosting Co-teaching with Compression Regularization for Label Noise | ✓ Link | 81.3 | Vgg19-BN | NO | CE + Dropout | 2021-04-28 |
| Boosting Co-teaching with Compression Regularization for Label Noise | ✓ Link | 81.3 | Vgg19-BN | NO | Nested Dropout | 2021-04-28 |
| Learning with Feature-Dependent Label Noise: A Progressive Approach | ✓ Link | 79.4 | Vgg19-BN | NO | Cross Entropy | 2021-03-13 |