% Key papers for Mixed-precision quantization (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2018_quantization_13494,
  title = {{Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Jacob_Quantization_and_Training_CVPR_2018_paper.html},
}

@inproceedings{cvpr2019_haq_14272,
  title = {{HAQ: Hardware-Aware Automated Quantization With Mixed Precision}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{iclr2017_trained_28299,
  title = {{Trained Ternary Quantization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=S1_pAu9xl},
}

@inproceedings{icml2016_fixed_35845,
  title = {{Fixed Point Quantization of Deep Convolutional Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/linb16.html},
}

@inproceedings{cvpr2017_deep_12157,
  title = {{Deep Learning With Low Precision by Half-Wave Gaussian Quantization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2017_incremental_28287,
  title = {{Incremental Network Quantization: Towards Lossless CNNs with Low-precision Weights}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=HyQJ-mclg},
}

@inproceedings{cvpr2019_learning_14449,
  title = {{Learning to Quantize Deep Networks by Optimizing Quantization Intervals With Task Loss}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2019_quantization_14685,
  title = {{Quantization Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_zeroq_16506,
  title = {{ZeroQ: A Novel Zero Shot Quantization Framework}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_learned_29837,
  title = {{LEARNED STEP SIZE QUANTIZATION}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rkgO66VKDS},
}

@inproceedings{cvpr2017_weighted_12756,
  title = {{Weighted-Entropy-Based Quantization for Deep Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2019_improving_37445,
  title = {{Improving Neural Network Quantization without Retraining using Outlier Channel Splitting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3981},
}

@inproceedings{neurips2018_scalable_57605,
  title = {{Scalable methods for 8-bit training of neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11503},
}

@inproceedings{aaai2018_adaptive_102356,
  title = {{Adaptive Quantization for Deep Neural Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11623},
}

@inproceedings{cvpr2020_towards_16367,
  title = {{Towards Unified INT8 Training for Convolutional Neural Network}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{cvpr2018_syq_13557,
  title = {{SYQ: Learning Symmetric Quantization for Efficient Deep Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Faraone_SYQ_Learning_Symmetric_CVPR_2018_paper.html},
}

@inproceedings{neurips2017_training_56737,
  title = {{Training Quantized Nets: A Deeper Understanding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9354},
}

@inproceedings{cvpr2018_two_13674,
  title = {{Two-Step Quantization for Low-Bit Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Wang_Two-Step_Quantization_for_CVPR_2018_paper.html},
}

@inproceedings{cvpr2020_adabits_15115,
  title = {{AdaBits: Neural Network Quantization With Adaptive Bit-Widths}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{iclr2020_additive_29342,
  title = {{Additive Powers-of-Two Quantization: An Efficient Non-uniform Discretization for Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BkgXT24tDS},
}

@inproceedings{aaai2024_towards_7590,
  title = {{Towards Efficient Verification of Quantized Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30108},
}

@inproceedings{cvpr2024_retraining_24644,
  title = {{Retraining-Free Model Quantization via One-Shot Weight-Coupling Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30845},
}

@inproceedings{aaai2025_jaq_9617,
  title = {{JAQ: Joint Efficient Architecture Design and Low-Bit Quantization with Hardware-Software Co-Exploration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35415},
}

@inproceedings{aaai2024_metamix_6634,
  title = {{MetaMix: Meta-State Precision Searcher for Mixed-Precision Activation Quantization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29212},
}

@inproceedings{neurips2025_efficient_75544,
  title = {{Efficient and Generalizable Mixed-Precision Quantization via Topological Entropy}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9Hweh7Wx8R},
}

@inproceedings{neurips2025_efficient_77557,
  title = {{Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=VBKgukQlRG},
}

@inproceedings{aaai2026_infoq_106732,
  title = {{InfoQ: Mixed-Precision Quantization via Global Information Flow}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39039},
}

@inproceedings{icml2024_a2q_45287,
  title = {{A2Q+: Improving Accumulator-Aware Weight Quantization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33165},
}

@inproceedings{icml2025_learning_48455,
  title = {{Learning from Loss Landscape: Generalizable Mixed-Precision Quantization via Adaptive Sharpness-Aware Gradient Aligning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44162},
}

@inproceedings{icml2025_matryoshka_48636,
  title = {{Matryoshka Quantization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43985},
}

@inproceedings{iclr2025_qinco2_80668,
  title = {{Qinco2: Vector Compression and Search with Improved Implicit Neural Codebooks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31099},
}

@inproceedings{iclr2026_compute_86522,
  title = {{Compute-Optimal Quantization-Aware Training}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=QpbtT95S95},
}

@inproceedings{aaai2026_double_106993,
  title = {{Double Rounding: Nearly Lossless Adaptive Bit Switching for QAT}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39345},
}

@inproceedings{aaai2026_on_107161,
  title = {{On the Impact of Weight Quantization on Deep Neural Network Uncertainty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39513},
}

@inproceedings{aaai2026_dqt_107365,
  title = {{DQT: Dynamic Quantization Training via Dequantization-Free Nested Integer Arithmetic}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39717},
}

@inproceedings{iclr2026_bbq_88997,
  title = {{BBQ: Boosting Quantization Entropy with Bell Box Quantization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=tY9yPAT3PU},
}

@inproceedings{neurips2026_precision_90750,
  title = {{Precision-Pyramid: Towards real-time neural decoding for fault-tolerant quantum computing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155454},
}