mlsanityData to 14 Oct 2026

A probabilistic framework for dynamic quantization

arXiv 2505.10689 ↗First posted 15 May 2025cs.LG cs.CVcited by 1

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Abstract (arXiv)

We propose a probabilistic framework for dynamic quantization of neural networks that allows for a computationally efficient input-adaptive rescaling of the quantization parameters. Our framework applies a probabilistic model to the network's pre-activations through a lightweight surrogate, enabling the adaptive adjustment of the quantization parameters on a per-input basis without significant memory overhead. We validate our approach on a set of popular computer vision tasks and models, observing only a negligible loss in performance. Our method strikes the best performance and computational overhead tradeoff compared to standard quantization strategies.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 25 of its 43 references that are in the map. First posted on arXiv 15 May 2025.

Builds on

25 of 43 references.

References · 25

  1. 2017Attention Is All You Needcited by 60,361
  2. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  5. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  6. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  7. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  8. 2023FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioningcited by 2,598
  9. 2013Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computationcited by 2,079
  10. 2024Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Modelcited by 1,056
  11. 2022Token Merging: Your ViT But Fastercited by 1,021
  12. 2017DOTA: A Large-scale Dataset for Object Detection in Aerial Imagescited by 623
13 more
  1. 2017Deep Neural Networks as Gaussian Processescited by 622
  2. 2018Quantizing deep convolutional networks for efficient inference: A whitepapercited by 521
  3. 2021A White Paper on Neural Network Quantizationcited by 472
  4. 2016Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activationscited by 426
  5. 2019HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precisioncited by 402
  6. 2020MCUNet: Tiny Deep Learning on IoT Devicescited by 273
  7. 2019HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networkscited by 261
  8. 2023EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attentioncited by 172
  9. 2020TensorFlow Lite Micro: Embedded Machine Learning on TinyML Systemscited by 165
  10. 2018CMSIS-NN: Efficient Neural Network Kernels for Arm Cortex-M CPUscited by 121
  11. 2021Differentiable Model Compression via Pseudo Quantization Noisecited by 45
  12. 2021MicroNet: Improving Image Recognition with Extremely Low FLOPscited by 26
  13. 2023Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learningcited by 17

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026TTQ: Activation-Aware Test-Time Quantization to Accelerate LLM Inference On The Flycited by 1

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