DUCKQUANT / THE QUANT & AI DIRECTORY
1,058 resources, ranked by in-directory PageRank
Y Chaurasia, P Desai, S Gujar - arXiv preprint arXiv:2406.13585, 2024 - arxiv.org. … While extracted, MEV might not always be high; there have…
D Malkhi, P Szalachowski - arXiv preprint arXiv:2208.00940, 2022 - arxiv.org. … The original work called the measure miner extractable value, which was later…
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Publication: Binary Neural Networks: A Survey. Published Mar 31, 2020.
Publication: A White Paper on Neural Network Quantization. Published Jun 15, 2021.
Publication: Full Stack Optimization of Transformer Inference: a Survey. Published Feb 27, 2023.
Publication: A Survey of Quantization Methods for Efficient Neural Network Inference. Published Mar 25, 2021.
Publication: Accurate LoRA-Finetuning Quantization of LLMs via Information Retention. Published Feb 8, 2024.
Publication: RepQuant: Towards Accurate Post-Training Quantization of Large Transformer Models via Scale Reparameterization. Published Feb 8, 2024.
Publication: Squat: Quant Small Language Models on the Edge. Published Feb 16, 2024.
Publication: APTQ: Attention-aware Post-Training Mixed-Precision Quantization for Large Language Models. Published Feb 21, 2024.
Publication: GPTVQ: The Blessing of Dimensionality for LLM Quantization. Published Feb 23, 2024.
Publication: A Comprehensive Evaluation of Quantization Strategies for Large Language Models. Published Feb 26, 2024.
Publication: FlattenQuant: Breaking Through the Inference Compute-bound for Large Language Models with Per-tensor Quantization. Published Feb 28, 2024.
Publication: IntactKV: Improving Large Language Model Quantization by Keeping Pivot Tokens Intact. Published Mar 2, 2024.
Publication: EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs. Published Mar 5, 2024.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Publication: ZeroQuant-HERO: Hardware-Enhanced Robust Optimized Post-Training Quantization Framework for W8A8 Transformers. Published Oct 26, 2023.
Publication: Atom: Low-bit Quantization for Efficient and Accurate LLM Serving. Published Oct 29, 2023.
Publication: QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models. Published Oct 25, 2023.
Publication: QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources. Published Oct 11, 2023.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Explore this resource at its source website for documentation and current information.
Publication: Fast and Efficient 2-bit LLM Inference on GPU: 2/4/16-bit in a Weight Matrix with Asynchronous Dequantization. Published Nov 28, 2023.
Publication: AFPQ: Asymmetric Floating Point Quantization for LLMs. Published Nov 3, 2023.
Publication: A Speed Odyssey for Deployable Quantization of LLMs. Published Nov 16, 2023.
Publication: SmoothQuant+: Accurate and Efficient 4-bit Post-Training WeightQuantization for LLM. Published Dec 6, 2023.
Publication: Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge. Published Dec 9, 2023.
