{"total":34,"rows":[{"id":"2101.05022","title":"Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels","created":"2021-01-13","cited_by_count":118,"area":null},{"id":"2108.06227","title":"SimCVD: Simple Contrastive Voxel-Wise Representation Distillation for Semi-Supervised Medical Image Segmentation","created":"2021-08-13","cited_by_count":86,"area":null},{"id":"2104.15092","title":"Faster Meta Update Strategy for Noise-Robust Deep Learning","created":"2021-04-30","cited_by_count":38,"area":null},{"id":"2404.07236","title":"Lightweight Deep Learning for Resource-Constrained Environments: A Survey","created":"2024-04-08","cited_by_count":38,"area":null},{"id":"2111.01026","title":"Introspective Distillation for Robust Question Answering","created":"2021-11-01","cited_by_count":25,"area":null},{"id":"2310.14277","title":"A Survey on Continual Semantic Segmentation: Theory, Challenge, Method and Application","created":"2023-10-22","cited_by_count":21,"area":null},{"id":"2301.13156","title":"SeaFormer++: Squeeze-enhanced Axial Transformer for Mobile Visual Recognition","created":"2023-01-30","cited_by_count":18,"area":null},{"id":"2107.00197","title":"Few-Shot Learning with a Strong Teacher","created":"2021-07-01","cited_by_count":16,"area":null},{"id":"2411.02793","title":"Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning","created":"2024-11-05","cited_by_count":16,"area":null},{"id":"2308.13998","title":"Computation-efficient Deep Learning for Computer Vision: A Survey","created":"2023-08-27","cited_by_count":14,"area":null},{"id":"2303.08983","title":"Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement","created":"2023-03-15","cited_by_count":11,"area":null},{"id":"2308.09105","title":"Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation","created":"2023-08-17","cited_by_count":10,"area":null},{"id":"2304.10113","title":"SATA: Source Anchoring and Target Alignment Network for Continual Test Time Adaptation","created":"2023-04-20","cited_by_count":8,"area":null},{"id":"2306.02090","title":"Deep Classifier Mimicry without Data Access","created":"2023-06-03","cited_by_count":6,"area":null},{"id":"2208.01302","title":"Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction","created":"2022-08-02","cited_by_count":4,"area":null},{"id":"2203.10923","title":"TinyMLOps: Operational Challenges for Widespread Edge AI Adoption","created":"2022-03-21","cited_by_count":3,"area":null},{"id":"2207.12660","title":"Bilateral Self-unbiased Learning from Biased Implicit Feedback","created":"2022-07-26","cited_by_count":3,"area":null},{"id":"2211.00683","title":"Reduce, Reuse, Recycle: Improving Training Efficiency with Distillation","created":"2022-11-01","cited_by_count":3,"area":null},{"id":"2301.11892","title":"Streaming LifeLong Learning With Any-Time Inference","created":"2023-01-27","cited_by_count":3,"area":null},{"id":"2303.12992","title":"A Survey of Historical Learning: Learning Models with Learning History","created":"2023-03-23","cited_by_count":3,"area":null},{"id":"2409.14538","title":"Towards Model-Agnostic Dataset Condensation by Heterogeneous Models","created":"2024-09-22","cited_by_count":3,"area":null},{"id":"2106.02242","title":"Scalable Transformers for Neural Machine Translation","created":"2021-06-04","cited_by_count":2,"area":null},{"id":"2107.07985","title":"Unpaired cross-modality educed distillation (CMEDL) for medical image segmentation","created":"2021-07-16","cited_by_count":2,"area":null},{"id":"2203.08390","title":"Reducing Flipping Errors in Deep Neural Networks","created":"2022-03-16","cited_by_count":2,"area":null},{"id":"2205.01620","title":"Unifying the Convergences in Multilingual Neural Machine Translation","created":"2022-05-03","cited_by_count":2,"area":null},{"id":"2606.03938","title":"q0: Primitives for Hyper-Epoch Pretraining","created":"2026-06-02","cited_by_count":2,"area":null},{"id":"2203.06474","title":"Optimizer Amalgamation","created":"2022-03-12","cited_by_count":1,"area":null},{"id":"2310.03188","title":"Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication","created":"2023-10-04","cited_by_count":1,"area":null},{"id":"2607.08164","title":"Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directions","created":"2026-07-09","cited_by_count":1,"area":null},{"id":"2211.13587","title":"Responsible Active Learning via Human-in-the-loop Peer Study","created":"2022-11-24","cited_by_count":0,"area":null},{"id":"2401.07469","title":"A Deep Hierarchical Feature Sparse Framework for Occluded Person Re-Identification","created":"2024-01-15","cited_by_count":0,"area":null},{"id":"2501.16329","title":"sDREAMER: Self-distilled Mixture-of-Modality-Experts Transformer for Automatic Sleep Staging","created":"2025-01-27","cited_by_count":0,"area":null},{"id":"2508.05404","title":"NT-ML: Backdoor Defense via Non-target Label Training and Mutual Learning","created":"2025-08-07","cited_by_count":0,"area":null},{"id":"2605.07420","title":"SR$^2$-LoRA: Self-Rectifying Inter-layer Relations in Low-Rank Adaptation for Class-Incremental Learning","created":"2026-05-08","cited_by_count":0,"area":null}],"next_cursor":null}