% Key papers for Fine-tuning strategies for few-shot (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2019_learning_29088,
  title = {{LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/976},
}

@inproceedings{cvpr2019_finding_14216,
  title = {{Finding Task-Relevant Features for Few-Shot Learning by Category Traversal}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2018_learning_13317,
  title = {{Learning to Compare: Relation Network for Few-Shot Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Sung_Learning_to_Compare_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_one_56540,
  title = {{One-Shot Imitation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8902},
}

@inproceedings{neurips2018_tadam_57673,
  title = {{TADAM: Task dependent adaptive metric for improved few-shot learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11094},
}

@inproceedings{cvpr2021_prototype_17670,
  title = {{Prototype Completion With Primitive Knowledge for Few-Shot Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2021_partial_1154,
  title = {{Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09594-partial-is-better-than-all-revisiting-fine-tuning-strategy-for-few-shot-learning/},
}

@inproceedings{neurips2020_interventional_60103,
  title = {{Interventional Few-Shot Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17631},
}

@inproceedings{aaai2022_contrastnet_1880,
  title = {{ContrastNet: A Contrastive Learning Framework for Few-Shot Text Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/10492-contrastnet-a-contrastive-learning-framework-for-few-shot-text-classification/},
}

@inproceedings{icml2019_tapnet_37781,
  title = {{TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4024},
}

@inproceedings{cvpr2021_eckpn_16926,
  title = {{ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-Shot Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2017_few_56318,
  title = {{Few-Shot Learning Through an Information Retrieval  Lens}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9013},
}

@inproceedings{aaai2021_few_617,
  title = {{Few-shot Learning for Multi-label Intent Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/13036-few-shot-learning-for-multi-label-intent-detection/},
}

@inproceedings{icml2020_laplacian_38360,
  title = {{Laplacian Regularized Few-Shot Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6480},
}

@inproceedings{aaai2022_inductive_2246,
  title = {{Inductive Relation Prediction by BERT}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05923-inductive-relation-prediction-by-bert/},
}

@inproceedings{cvpr2021_reinforced_17730,
  title = {{Reinforced Attention for Few-Shot Learning and Beyond}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{neurips2020_information_60084,
  title = {{Information Maximization for Few-Shot Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17400},
}

@inproceedings{cvpr2022_a_18201,
  title = {{A Hybrid Egocentric Activity Anticipation Framework via Memory-Augmented Recurrent and One-Shot Representation Forecasting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2022_alp_1692,
  title = {{ALP: Data Augmentation Using Lexicalized PCFGs for Few-Shot Text Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/10894-alp-data-augmentation-using-lexicalized-pcfgs-for-few-shot-text-classification/},
}

@inproceedings{icml2023_the_43229,
  title = {{The Unreasonable Effectiveness of Few-shot Learning for Machine Translation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23572},
}

@inproceedings{cvpr2025_few_26256,
  title = {{Few-shot Personalized Scanpath Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35150},
}

@inproceedings{cvpr2025_osloprompt_27101,
  title = {{OSLoPrompt: Bridging Low-Supervision Challenges and Open-Set Domain Generalization in CLIP}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33907},
}

@inproceedings{neurips2024_meta_70300,
  title = {{Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96793},
}

@inproceedings{aaai2024_few_6010,
  title = {{Few-Shot Learning via Repurposing Ensemble of Black-Box Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29137},
}

@inproceedings{iclr2024_towards_33499,
  title = {{Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19576},
}

@inproceedings{cvpr2025_cobra_25660,
  title = {{COBRA: COmBinatorial Retrieval Augmentation for Few-Shot Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34338},
}

@inproceedings{iclr2024_one_33962,
  title = {{One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19113},
}

@inproceedings{icml2024_learning_44188,
  title = {{Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34264},
}

@inproceedings{icml2026_caos_53649,
  title = {{CAOS: Conformal Aggregation of One-Shot Predictors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=hQoT2F37Am},
}

@inproceedings{neurips2026_epiplexity_90387,
  title = {{Epiplexity Guided Data Selection and Generation for Out-of-Distribution Generalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153698},
}

@inproceedings{aaai2026_incorporating_108214,
  title = {{Incorporating Token Importance in Multi-Vector Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40566},
}

@inproceedings{iclr2024_scalable_35291,
  title = {{Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17782},
}

@inproceedings{icml2026_bicrossnet_49805,
  title = {{BiCrossNet with Decoupled Dual Generators: A Parameter‑Efficient and Generalizable Few‑Shot Custom Gesture Recognition Framework}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5spu7QlKUd},
}

@inproceedings{icml2026_bayes_50083,
  title = {{Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8uqxbSPlkn},
}

@inproceedings{icml2026_weight_50236,
  title = {{Weight-Space Learning for Certifiable Few-shot Transfer Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=AMIV24ianZ},
}

@inproceedings{aaai2026_active_108914,
  title = {{Active Learning for Animal Re-Identification with Ambiguity-Aware Sampling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/41266},
}