% Key papers for Hierarchical VQ-VAE generation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2018_a_12812,
  title = {{A Variational U-Net for Conditional Appearance and Shape Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Esser_A_Variational_U-Net_CVPR_2018_paper.html},
}

@inproceedings{cvpr2024_efficient_23328,
  title = {{Efficient Deformable ConvNets: Rethinking Dynamic and Sparse Operator for Vision Applications}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31637},
}

@inproceedings{cvpr2017_learning_12401,
  title = {{Learning Diverse Image Colorization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2017_toward_36432,
  title = {{Toward Controlled Generation of Text}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/816},
}

@inproceedings{neurips2017_diverse_56261,
  title = {{Diverse and Accurate Image Description Using a Variational Auto-Encoder with an Additive Gaussian Encoding Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9349},
}

@inproceedings{neurips2019_generating_58330,
  title = {{Generating Diverse High-Fidelity Images with VQ-VAE-2}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14395},
}

@inproceedings{neurips2016_towards_56055,
  title = {{Towards Conceptual Compression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7110},
}

@inproceedings{iclr2022_vector_31699,
  title = {{Vector-quantized Image Modeling with Improved VQGAN}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6405},
}

@inproceedings{cvpr2021_dual_16907,
  title = {{Dual Contradistinctive Generative Autoencoder}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{icml2020_controlvae_38050,
  title = {{ControlVAE: Controllable Variational Autoencoder}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6510},
}

@inproceedings{neurips2021_d2c_61330,
  title = {{D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27815},
}

@inproceedings{cvpr2023_catch_20571,
  title = {{Catch Missing Details: Image Reconstruction With Frequency Augmented Variational Autoencoder}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22768},
}

@inproceedings{cvpr2023_regularized_22023,
  title = {{Regularized Vector Quantization for Tokenized Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22534},
}

@inproceedings{neurips2016_an_55572,
  title = {{An Architecture for Deep, Hierarchical Generative Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/8503},
}

@inproceedings{neurips2020_hierarchical_60004,
  title = {{Hierarchical Quantized Autoencoders}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17043},
}

@inproceedings{cvpr2022_global_18942,
  title = {{Global Context With Discrete Diffusion in Vector Quantised Modelling for Image Generation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{iclr2021_modals_30400,
  title = {{MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2589},
}

@inproceedings{cvpr2024_don_23255,
  title = {{Don't Look into the Dark: Latent Codes for Pluralistic Image Inpainting}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30081},
}

@inproceedings{iclr2019_overcoming_28938,
  title = {{Overcoming the Disentanglement vs Reconstruction Trade-off via Jacobian Supervision}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/1110},
}

@inproceedings{cvpr2021_patchwise_17591,
  title = {{Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2025_softvq_27704,
  title = {{SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32526},
}

@inproceedings{cvpr2024_rethinking_24640,
  title = {{Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29222},
}

@inproceedings{aaai2024_topic_7571,
  title = {{Topic-VQ-VAE: Leveraging Latent Codebooks for Flexible Topic-Guided Document Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29913},
}

@inproceedings{cvpr2025_mergevq_26942,
  title = {{MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33318},
}

@inproceedings{aaai2025_ssc_10634,
  title = {{SSC-VAE: Structured Sparse Coding Based Variational Autoencoder for Detail Preserved Image Reconstruction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32825},
}

@inproceedings{iclr2025_adaptive_83358,
  title = {{Adaptive Length Image Tokenization via Recurrent Allocation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28458},
}

@inproceedings{aaai2026_vaevq_105283,
  title = {{VAEVQ: Enhancing Discrete Visual Tokenization Through Variational Modeling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38155},
}

@inproceedings{icml2025_learnings_47057,
  title = {{Learnings from Scaling Visual Tokenizers for Reconstruction and Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45528},
}

@inproceedings{icml2025_eq_47482,
  title = {{EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45112},
}

@inproceedings{icml2025_epsilon_48553,
  title = {{Epsilon-VAE: Denoising as Visual Decoding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44068},
}

@inproceedings{icml2026_arcvq_50049,
  title = {{ArcVQ-VAE: A Spherical Vector Quantization Framework with ArcCosine Additive Margin}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8YoP649pGC},
}

@inproceedings{icml2026_star_52041,
  title = {{STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=SDWG5xr20c},
}

@inproceedings{icml2026_the_53198,
  title = {{The Latent Color Subspace: Emergent Order in High-Dimensional Chaos}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=d93mcbLGhV},
}

@inproceedings{icml2026_distribution_54704,
  title = {{Distribution Matching Variational AutoEncoder}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=re1J8BPwTQ},
}

@inproceedings{neurips2025_sparse_80161,
  title = {{Sparse Image Synthesis via Joint Latent and RoI Flow}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=wq5G71w7Zx},
}

@inproceedings{iclr2025_bringing_81785,
  title = {{Bringing NeRFs to the Latent Space: Inverse Graphics Autoencoder}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29995},
}

@inproceedings{iclr2026_latent_84356,
  title = {{Latent Denoising Makes Good Tokenizers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=1jBsi98fVe},
}

@inproceedings{iclr2026_product_85318,
  title = {{Product-Quantised Image Representation for High-Quality Image Synthesis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=D8oqcochgq},
}