% Key papers for Few-shot and metric distillation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_self_16215,
  title = {{Self-Training With Noisy Student Improves ImageNet Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2020_dreaming_15439,
  title = {{Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2022_learning_19193,
  title = {{Learning Multiple Adverse Weather Removal via Two-Stage Knowledge Learning and Multi-Contrastive Regularization: Toward a Unified Model}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2018_darkrank_102516,
  title = {{DarkRank: Accelerating Deep Metric Learning via Cross Sample Similarities Transfer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11783},
}

@inproceedings{aaai2016_face_105396,
  title = {{Face Model Compression by Distilling Knowledge from Neurons}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10449},
}

@inproceedings{aaai2019_meal_101702,
  title = {{MEAL: Multi-Model Ensemble via Adversarial Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4417},
}

@inproceedings{cvpr2020_inter_15699,
  title = {{Inter-Region Affinity Distillation for Road Marking Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2019_learning_14406,
  title = {{Learning Metrics From Teachers: Compact Networks for Image Embedding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{aaai2019_amalgamating_101364,
  title = {{Amalgamating Knowledge towards Comprehensive Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4165},
}

@inproceedings{neurips2018_paraphrasing_57501,
  title = {{Paraphrasing Complex Network: Network Compression via Factor Transfer}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11283},
}

@inproceedings{cvpr2019_student_14883,
  title = {{Student Becoming the Master: Knowledge Amalgamation for Joint Scene Parsing, Depth Estimation, and More}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2022_how_19009,
  title = {{How Many Observations Are Enough? Knowledge Distillation for Trajectory Forecasting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2024_clip_22916,
  title = {{CLIP-KD: An Empirical Study of CLIP Model Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31005},
}

@inproceedings{aaai2022_add_1690,
  title = {{ADD: Frequency Attention and Multi-View Based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/00122-add-frequency-attention-and-multi-view-based-knowledge-distillation-to-detect-low-quality-compressed-deepfake-images/},
}

@inproceedings{cvpr2023_masked_21533,
  title = {{Masked Autoencoders Enable Efficient Knowledge Distillers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/20963},
}

@inproceedings{iclr2021_knowledge_30427,
  title = {{Knowledge distillation via softmax regression representation learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2531},
}

@inproceedings{cvpr2020_neural_15944,
  title = {{Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation From a Blackbox Model}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2023_rethinking_22044,
  title = {{Rethinking Feature-Based Knowledge Distillation for Face Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22607},
}

@inproceedings{aaai2020_few_101858,
  title = {{Few Shot Network Compression via Cross Distillation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5718},
}

@inproceedings{aaai2021_progressive_1199,
  title = {{Progressive Network Grafting for Few-Shot Knowledge Distillation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/02541-progressive-network-grafting-for-few-shot-knowledge-distillation/},
}

@inproceedings{cvpr2024_asymmetric_22786,
  title = {{Asymmetric Masked Distillation for Pre-Training Small Foundation Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31881},
}

@inproceedings{aaai2025_reinforced_10501,
  title = {{Reinforced Multi-teacher Knowledge Distillation for Efficient General Image Forgery Detection and Localization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32085},
}

@inproceedings{aaai2025_mtvhunter_9880,
  title = {{MTVHunter: Smart Contracts Vulnerability Detection Based on Multi-Teacher Knowledge Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33664},
}

@inproceedings{cvpr2025_customkd_25808,
  title = {{CustomKD: Customizing Large Vision Foundation for Edge Model Improvement via Knowledge Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33293},
}

@inproceedings{aaai2025_codts_8430,
  title = {{CoDTS: Enhancing Sparsely Supervised Collaborative Perception with a Dual Teacher-Student Framework}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32348},
}

@inproceedings{neurips2024_udon_73464,
  title = {{UDON: Universal Dynamic Online distillatioN for generic image representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94005},
}

@inproceedings{aaai2026_revisiting_104257,
  title = {{Revisiting Cross-Architecture Distillation: Adaptive Dual-Teacher Transfer for Lightweight Video Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37786},
}

@inproceedings{icml2026_regret_50755,
  title = {{Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=FNZs7SLEEI},
}

@inproceedings{neurips2025_learning_80154,
  title = {{Learning Task-Agnostic Representations through Multi-Teacher Distillation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=wmkd9qYty4},
}

@inproceedings{iclr2025_accessing_81768,
  title = {{Accessing Vision Foundation Models via ImageNet-1K}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30012},
}

@inproceedings{iclr2025_swiss_82888,
  title = {{Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28912},
}

@inproceedings{iclr2026_boomerang_84610,
  title = {{Boomerang Distillation Enables Zero-Shot Model Size Interpolation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=4ZU8v4s3IR},
}

@inproceedings{iclr2026_learning_85972,
  title = {{Learning Shrinks the Hard Tail: Training‑Dependent Inference Scaling in a Solvable Linear Model}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=KUNywR7nQx},
}

@inproceedings{iclr2026_singer_87744,
  title = {{SiNGER: A Clearer Voice Distills Vision Transformers Further}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=exjrxVc2yT},
}

@inproceedings{iclr2026_bird_88144,
  title = {{BIRD: Behavior Induction via Representation-structure Distillation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=jbJGhHpwmJ},
}

@inproceedings{neurips2026_identified_90748,
  title = {{Identified-Set Geometry of Distributional Model Extraction under Top-K Censored API Access}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149969},
}

@inproceedings{neurips2026_understanding_91759,
  title = {{Understanding Layer Patching in Model Size Interpolation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152284},
}

@inproceedings{neurips2026_deltaprompts_92933,
  title = {{DeltaPrompts: Escaping the Zero-Delta Trap in Multimodal Distillation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153494},
}

@inproceedings{neurips2026_closed_93226,
  title = {{Closed-Form Linear-Probe Dataset Distillation for Pre-trained Vision Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153458},
}