Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization
Fuente:
arXiv
Guardado en:
| Autores principales: | Egiazarian, Vage, Castro, Roberto L., Kuznedelev, Denis, Panferov, Andrei, Kurtic, Eldar, Pandit, Shubhra, Marques, Alexandre, Kurtz, Mark, Ashkboos, Saleh, Hoefler, Torsten, Alistarh, Dan |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
"Give Me BF16 or Give Me Death"? Accuracy-Performance Trade-Offs in LLM Quantization
por: Kurtic, Eldar, et al.
Publicado: (2024)
por: Kurtic, Eldar, et al.
Publicado: (2024)
Extreme Compression of Large Language Models via Additive Quantization
por: Egiazarian, Vage, et al.
Publicado: (2024)
por: Egiazarian, Vage, et al.
Publicado: (2024)
Grid Games: The Power of Multiple Grids for Quantizing Large Language Models
por: Egiazarian, Vage, et al.
Publicado: (2026)
por: Egiazarian, Vage, et al.
Publicado: (2026)
EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
por: Sieberling, Oliver, et al.
Publicado: (2024)
por: Sieberling, Oliver, et al.
Publicado: (2024)
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
por: Chen, Jiale, et al.
Publicado: (2025)
por: Chen, Jiale, et al.
Publicado: (2025)
Beyond Outliers: A Study of Optimizers Under Quantization
por: Vlassis, Georgios, et al.
Publicado: (2025)
por: Vlassis, Georgios, et al.
Publicado: (2025)
Statistically-Lossless Quantization of Large Language Models
por: Helcig, Michael, et al.
Publicado: (2026)
por: Helcig, Michael, et al.
Publicado: (2026)
Quartet: Native FP4 Training Can Be Optimal for Large Language Models
por: Castro, Roberto L., et al.
Publicado: (2025)
por: Castro, Roberto L., et al.
Publicado: (2025)
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
por: Shutova, Alina, et al.
Publicado: (2025)
por: Shutova, Alina, et al.
Publicado: (2025)
Accurate Compression of Text-to-Image Diffusion Models via Vector Quantization
por: Egiazarian, Vage, et al.
Publicado: (2024)
por: Egiazarian, Vage, et al.
Publicado: (2024)
Unified Scaling Laws for Compressed Representations
por: Panferov, Andrei, et al.
Publicado: (2025)
por: Panferov, Andrei, et al.
Publicado: (2025)
EfQAT: An Efficient Framework for Quantization-Aware Training
por: Ashkboos, Saleh, et al.
Publicado: (2024)
por: Ashkboos, Saleh, et al.
Publicado: (2024)
Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on Large Language Models
por: Kurtic, Eldar, et al.
Publicado: (2024)
por: Kurtic, Eldar, et al.
Publicado: (2024)
Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment
por: Agarwalla, Abhinav, et al.
Publicado: (2024)
por: Agarwalla, Abhinav, et al.
Publicado: (2024)
HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs
por: Ashkboos, Saleh, et al.
Publicado: (2025)
por: Ashkboos, Saleh, et al.
Publicado: (2025)
Apertus LLM Family Expansion via Distillation and Quantization
por: Panferov, Andrei, et al.
Publicado: (2026)
por: Panferov, Andrei, et al.
Publicado: (2026)
Panza: Design and Analysis of a Fully-Local Personalized Text Writing Assistant
por: Nicolicioiu, Armand, et al.
Publicado: (2024)
por: Nicolicioiu, Armand, et al.
Publicado: (2024)
Hogwild! Inference: Parallel LLM Generation via Concurrent Attention
por: Rodionov, Gleb, et al.
Publicado: (2025)
por: Rodionov, Gleb, et al.
Publicado: (2025)
CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training
por: Tabesh, Soroush, et al.
Publicado: (2025)
por: Tabesh, Soroush, et al.
Publicado: (2025)
GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
por: Dadgarnia, Alireza, et al.
Publicado: (2026)
por: Dadgarnia, Alireza, et al.
Publicado: (2026)
DarwinLM: Evolutionary Structured Pruning of Large Language Models
por: Tang, Shengkun, et al.
Publicado: (2025)
por: Tang, Shengkun, et al.
Publicado: (2025)
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
por: Malinovskii, Vladimir, et al.
Publicado: (2024)
por: Malinovskii, Vladimir, et al.
Publicado: (2024)
Error Feedback Can Accurately Compress Preconditioners
por: Modoranu, Ionut-Vlad, et al.
Publicado: (2023)
por: Modoranu, Ionut-Vlad, et al.
Publicado: (2023)
DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization
por: Lin, Haokun, et al.
Publicado: (2026)
por: Lin, Haokun, et al.
Publicado: (2026)
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
por: Ashkboos, Saleh, et al.
Publicado: (2024)
por: Ashkboos, Saleh, et al.
Publicado: (2024)
The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm
por: Chen, Jiale, et al.
Publicado: (2025)
por: Chen, Jiale, et al.
Publicado: (2025)
Quartet II: Accurate LLM Pre-Training in NVFP4 by Improved Unbiased Gradient Estimation
por: Panferov, Andrei, et al.
Publicado: (2026)
por: Panferov, Andrei, et al.
Publicado: (2026)
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
por: Ashkboos, Saleh, et al.
Publicado: (2024)
por: Ashkboos, Saleh, et al.
Publicado: (2024)
MicroAdam: Accurate Adaptive Optimization with Low Space Overhead and Provable Convergence
por: Modoranu, Ionut-Vlad, et al.
Publicado: (2024)
por: Modoranu, Ionut-Vlad, et al.
Publicado: (2024)
Correlated Quantization for Faster Nonconvex Distributed Optimization
por: Panferov, Andrei, et al.
Publicado: (2024)
por: Panferov, Andrei, et al.
Publicado: (2024)
The Iterative Optimal Brain Surgeon: Faster Sparse Recovery by Leveraging Second-Order Information
por: Wu, Diyuan, et al.
Publicado: (2024)
por: Wu, Diyuan, et al.
Publicado: (2024)
MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling
por: Zhang, Yu, et al.
Publicado: (2025)
por: Zhang, Yu, et al.
Publicado: (2025)
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
por: Panferov, Andrei, et al.
Publicado: (2025)
por: Panferov, Andrei, et al.
Publicado: (2025)
MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
por: Frantar, Elias, et al.
Publicado: (2024)
por: Frantar, Elias, et al.
Publicado: (2024)
SageAttention3: Microscaling FP4 Attention for Inference and An Exploration of 8-Bit Training
por: Zhang, Jintao, et al.
Publicado: (2025)
por: Zhang, Jintao, et al.
Publicado: (2025)
PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression
por: Malinovskii, Vladimir, et al.
Publicado: (2024)
por: Malinovskii, Vladimir, et al.
Publicado: (2024)
Neural Optimal Transport with General Cost Functionals
por: Asadulaev, Arip, et al.
Publicado: (2022)
por: Asadulaev, Arip, et al.
Publicado: (2022)
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
por: Li, Shigang, et al.
Publicado: (2019)
por: Li, Shigang, et al.
Publicado: (2019)
LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs
por: Gordon, Ofir, et al.
Publicado: (2026)
por: Gordon, Ofir, et al.
Publicado: (2026)
Post Training Quantization of Large Language Models with Microscaling Formats
por: Sharify, Sayeh, et al.
Publicado: (2024)
por: Sharify, Sayeh, et al.
Publicado: (2024)
Ejemplares similares
-
"Give Me BF16 or Give Me Death"? Accuracy-Performance Trade-Offs in LLM Quantization
por: Kurtic, Eldar, et al.
Publicado: (2024) -
Extreme Compression of Large Language Models via Additive Quantization
por: Egiazarian, Vage, et al.
Publicado: (2024) -
Grid Games: The Power of Multiple Grids for Quantizing Large Language Models
por: Egiazarian, Vage, et al.
Publicado: (2026) -
EvoPress: Accurate Dynamic Model Compression via Evolutionary Search
por: Sieberling, Oliver, et al.
Publicado: (2024) -
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
por: Chen, Jiale, et al.
Publicado: (2025)