Zhen-Dong/Awesome-Quantization-Papers

• highreadme#1

  Emphasize "awesome list" nature in README opening

  Why:

  CURRENT

  This repo contains a comprehensive paper list of **Model Quantization** for efficient deep learning on AI conferences/journals/arXiv.

  COPY-PASTE FIX

  Copy

  This **awesome list** is a comprehensive, curated collection of papers on **Model Quantization** for efficient deep learning across AI conferences, journals, and arXiv.

  OpenDoneDismiss
• mediumhomepage#2

  Add repository URL as homepage

  Why:

  COPY-PASTE FIX

  Copy

  https://github.com/Zhen-Dong/Awesome-Quantization-Papers

  OpenDoneDismiss
• lowreadme#3

  Add a "How to Use" section to the README

  Why:

  COPY-PASTE FIX

  Copy

  ## How to Use This List
  
  This repository is organized to help you quickly find relevant papers. Papers are categorized by model structures and application scenarios, and labeled with keywords. Use the table of contents to navigate or search within the document for specific topics or authors.

  OpenDoneDismiss

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  Where can I find recent research papers on neural network quantization for efficient edge inference?

  you: not recommended
  AI recommended (in order):

  1. arXiv.org
  2. Google Scholar
  3. NeurIPS
  4. ICLR
  5. CVPR
  6. ECCV
  7. ICCV
  8. MLSys
  9. TinyML Research Symposium
  10. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  11. Journal of Machine Learning Research (JMLR)
  12. Nature Machine Intelligence
  13. Nature Communications
  14. GitHub
  15. Connected Papers
  16. Semantic Scholar

  AI recommended 16 alternatives but never named Zhen-Dong/Awesome-Quantization-Papers. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  What are the latest research papers on quantization techniques applied to large language models?

  you: not recommended
  AI recommended (in order):

  1. AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
  2. LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
  3. GPTQ: Accurate Post-training Quantization for Generative Pre-trained Transformers
  4. QLoRA: Efficient Finetuning of Quantized LLMs on Consumer GPUs
  5. SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Quantization
  6. Outlier-Aware Quantization for LLMs
  7. SqueezeLLM: Dense-and-Sparse Quantization for Large Language Models

  AI recommended 7 alternatives but never named Zhen-Dong/Awesome-Quantization-Papers. This is the gap to close.

  Show full AI answer

• Metadata completeness

  warn

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of Zhen-Dong/Awesome-Quantization-Papers?

  pass
  ✓AI named Zhen-Dong/Awesome-Quantization-Papers explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts Zhen-Dong/Awesome-Quantization-Papers in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI named Zhen-Dong/Awesome-Quantization-Papers explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo Zhen-Dong/Awesome-Quantization-Papers solve, and who is the primary audience?

  pass
  ⚠AI did not name Zhen-Dong/Awesome-Quantization-Papers — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?