% Key papers for Mixture and distillation for domain shift (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2019_learning_58504,
  title = {{Learning Robust Global Representations by Penalizing Local Predictive Power}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14061},
}

@inproceedings{aaai2016_multi_105119,
  title = {{Multi-Domain Active Learning for Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10291},
}

@inproceedings{aaai2021_deep_399,
  title = {{Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04010-deep-transfer-tensor-decomposition-with-orthogonal-constraint-for-recommender-systems/},
}

@inproceedings{icml2018_modeling_36857,
  title = {{Modeling Sparse Deviations for Compressed Sensing using Generative Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2331},
}

@inproceedings{aaai2022_multiplexnet_2450,
  title = {{MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05700-multiplexnet-towards-fully-satisfied-logical-constraints-in-neural-networks/},
}

@inproceedings{cvpr2019_efficient_14133,
  title = {{Efficient Multi-Domain Learning by Covariance Normalization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{aaai2024_model_6661,
  title = {{Model Reprogramming: Resource-Efficient Cross-Domain Machine Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30267},
}

@inproceedings{icml2018_jointgan_36764,
  title = {{JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2161},
}

@inproceedings{aaai2021_finding_620,
  title = {{Finding Sparse Structures for Domain Specific Neural Machine Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/13333-finding-sparse-structures-for-domain-specific-neural-machine-translation/},
}

@inproceedings{neurips2022_sym_65804,
  title = {{Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55085},
}

@inproceedings{iclr2022_leveraging_31684,
  title = {{Leveraging unlabeled data to predict out-of-distribution performance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6847},
}

@inproceedings{aaai2025_mtl_9879,
  title = {{MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35509},
}

@inproceedings{icml2020_ltf_38357,
  title = {{LTF: A Label Transformation Framework for Correcting Label Shift}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5962},
}

@inproceedings{neurips2022_meta_65346,
  title = {{Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-Experts}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53676},
}

@inproceedings{aaai2023_cross_3362,
  title = {{Cross-Domain Adaptative Learning for Online Advertisement Customer Lifetime Value Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25583},
}

@inproceedings{neurips2023_doremi_69312,
  title = {{DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70588},
}

@inproceedings{aaai2022_mdd_2385,
  title = {{MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/11657-mdd-eval-self-training-on-augmented-data-for-multi-domain-dialogue-evaluation/},
}

@inproceedings{icml2018_radialgan_36948,
  title = {{RadialGAN: Leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2027},
}

@inproceedings{aaai2021_cfq_1,
  title = {{*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09949-cfq-analyzing-the-scalability-of-machine-learning-on-a-compositional-task/},
}

@inproceedings{aaai2023_towards_4830,
  title = {{Towards Automated Modeling Assistance: An Efficient Approach for Repairing Flawed Planning Domains}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26418},
}

@inproceedings{cvpr2024_domain_23248,
  title = {{Domain Gap Embeddings for Generative Dataset Augmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31369},
}

@inproceedings{aaai2024_domain_5743,
  title = {{Domain-Aware Fine-Tuning: Enhancing Neural Network Adaptability}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29116},
}

@inproceedings{cvpr2024_map_24051,
  title = {{MAP: MAsk-Pruning for Source-Free Model Intellectual Property Protection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30832},
}

@inproceedings{aaai2024_an_5177,
  title = {{An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27806},
}

@inproceedings{aaai2024_fairness_5965,
  title = {{Fairness without Demographics through Shared Latent Space-Based Debiasing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29167},
}

@inproceedings{aaai2024_naruto_6739,
  title = {{NaRuto: Automatically Acquiring Planning Models from Narrative Texts}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29999},
}

@inproceedings{aaai2024_decoupled_5629,
  title = {{Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29492},
}

@inproceedings{aaai2024_consistency_5475,
  title = {{Consistency-Guided Temperature Scaling Using Style and Content Information for Out-of-Domain Calibration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29041},
}

@inproceedings{iclr2024_bayesprompt_33948,
  title = {{BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19127},
}

@inproceedings{iclr2024_adapting_35427,
  title = {{Adapting to Distribution Shift by Visual Domain Prompt Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17646},
}

@inproceedings{aaai2024_when_7818,
  title = {{When Sparse Graph Representation Learning Falls into Domain Shift: Data Augmentation for Cross-Domain Graph Meta-Learning (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30489},
}

@inproceedings{aaai2025_learning_9727,
  title = {{Learning Cross-Domain Representations for Transferable Drug Perturbations on Single-Cell Transcriptional Responses}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34073},
}

@inproceedings{icml2024_exploring_44246,
  title = {{Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34206},
}

@inproceedings{neurips2024_beyond_71334,
  title = {{Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95914},
}

@inproceedings{neurips2025_conformal_74929,
  title = {{Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2bgwni6Ber},
}

@inproceedings{aaai2025_a_7937,
  title = {{A Unified Framework for Human-Allied Learning of Probabilistic Circuits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33955},
}

@inproceedings{aaai2025_assessing_8151,
  title = {{Assessing the Impact of Population Data Domain Differences on Transfer Learning in P300-based Brain-Computer Interfaces (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35271},
}

@inproceedings{iclr2024_tram_35120,
  title = {{TRAM: Bridging Trust Regions and Sharpness Aware Minimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17953},
}