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

@inproceedings{iclr2018_mixed_28661,
  title = {{Mixed Precision Training}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/288},
}

@inproceedings{cvpr2018_towards_13657,
  title = {{Towards Effective Low-Bitwidth Convolutional Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Zhuang_Towards_Effective_Low-Bitwidth_CVPR_2018_paper.html},
}

@inproceedings{aaai2018_extremely_102446,
  title = {{Extremely Low Bit Neural Network: Squeeze the Last Bit Out With ADMM}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11713},
}

@inproceedings{iclr2018_wrpn_28409,
  title = {{WRPN: Wide Reduced-Precision Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/208},
}

@inproceedings{neurips2018_training_57725,
  title = {{Training Deep Neural Networks with 8-bit Floating Point Numbers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11737},
}

@inproceedings{neurips2017_flexpoint_56326,
  title = {{Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8964},
}

@inproceedings{neurips2019_hybrid_58377,
  title = {{Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13636},
}

@inproceedings{cvpr2020_rethinking_16118,
  title = {{Rethinking Differentiable Search for Mixed-Precision Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2017_zipml_36461,
  title = {{ZipML: Training Linear Models with End-to-End Low Precision, and a Little Bit of Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/659},
}

@inproceedings{neurips2020_ultra_61024,
  title = {{Ultra-Low Precision 4-bit Training of Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17518},
}

@inproceedings{neurips2022_on_66498,
  title = {{On-Device Training Under 256KB Memory}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55026},
}

@inproceedings{aaai2021_any_137,
  title = {{Any-Precision Deep Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/10763-any-precision-deep-neural-networks/},
}

@inproceedings{iclr2018_training_28726,
  title = {{Training wide residual networks for deployment using a single bit for each weight}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/311},
}

@inproceedings{aaai2018_computation_106139,
  title = {{Computation Error Analysis of Block Floating Point Arithmetic Oriented Convolution Neural Network Accelerator Design}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11334},
}

@inproceedings{neurips2022_quantized_64302,
  title = {{Quantized Training of Gradient Boosting Decision Trees}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53370},
}

@inproceedings{iclr2021_a_30025,
  title = {{A Block Minifloat Representation for Training Deep Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2795},
}

@inproceedings{neurips2022_fp8_64473,
  title = {{FP8 Quantization: The Power of the Exponent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53073},
}

@inproceedings{icml2021_actnn_39015,
  title = {{ActNN: Reducing Training Memory Footprint via 2-Bit Activation Compressed Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9443},
}

@inproceedings{icml2020_multi_38474,
  title = {{Multi-Precision Policy Enforced Training (MuPPET) : A Precision-Switching Strategy for Quantised Fixed-Point Training of CNNs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6250},
}

@inproceedings{neurips2023_training_67567,
  title = {{Training Transformers with 4-bit Integers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72173},
}

@inproceedings{cvpr2024_pikelpn_24468,
  title = {{PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31868},
}

@inproceedings{neurips2025_analog_80463,
  title = {{Analog Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=zo4zYTR8vn},
}

@inproceedings{cvpr2025_towards_27912,
  title = {{Towards Lossless Implicit Neural Representation via Bit Plane Decomposition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33459},
}

@inproceedings{neurips2024_bold_71130,
  title = {{BOLD: Boolean Logic Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96092},
}

@inproceedings{iclr2024_towards_35254,
  title = {{Towards Cheaper Inference in Deep Networks with Lower Bit-Width Accumulators}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17819},
}

@inproceedings{icml2024_collage_44181,
  title = {{Collage: Light-Weight Low-Precision Strategy for LLM Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34271},
}

@inproceedings{icml2024_im_44795,
  title = {{IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33657},
}

@inproceedings{icml2025_scaling_46267,
  title = {{Scaling Laws for Floating–Point Quantization Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46293},
}

@inproceedings{icml2025_oscillation_46995,
  title = {{Oscillation-Reduced MXFP4 Training for Vision Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45588},
}

@inproceedings{icml2026_flashoptim_52503,
  title = {{FlashOptim: Optimizers for Memory-Efficient Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Wfe1iJocjF},
}

@inproceedings{icml2026_m_52626,
  title = {{M+Adam: Low-Precision Training via Additive–Multiplicative Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=XgVv56Y829},
}

@inproceedings{neurips2025_duo_80073,
  title = {{DUO: No Compromise to Accuracy Degradation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=vvEVQrm9M8},
}

@inproceedings{neurips2025_falqon_80325,
  title = {{FALQON: Accelerating LoRA Fine-tuning with Low-Bit Floating-Point Arithmetic}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=yPXOfBoQL7},
}

@inproceedings{icml2024_ampa_43996,
  title = {{AMPA: Adaptive Mixed Precision Allocation for Low-Bit Integer Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34456},
}

@inproceedings{icml2026_precision_55459,
  title = {{Precision-Induced Miscalibration: Understanding and Correcting Confidence Distortion in Quantized Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=zCkFbxKeF5},
}

@inproceedings{neurips2024_4_70946,
  title = {{4-bit Shampoo for Memory-Efficient Network Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96257},
}

@inproceedings{iclr2025_coat_82497,
  title = {{COAT: Compressing Optimizer states and Activations for Memory-Efficient FP8 Training}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29297},
}

@inproceedings{iclr2026_to_87066,
  title = {{To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=XI1CeufywD},
}

@inproceedings{neurips2026_angular_93903,
  title = {{Angular Networks: Low-Bit Learning from Randomized Similarity Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154802},
}