Beyond Outliers: A Study of Optimizers Under Quantization
Fuente:
arXiv
Saved in:
| Main Authors: | Vlassis, Georgios, Ashkboos, Saleh, Volkova, Alexandra, Hoefler, Torsten, Alistarh, Dan |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs
by: Ashkboos, Saleh, et al.
Published: (2025)
by: Ashkboos, Saleh, et al.
Published: (2025)
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
by: Ashkboos, Saleh, et al.
Published: (2024)
by: Ashkboos, Saleh, et al.
Published: (2024)
EfQAT: An Efficient Framework for Quantization-Aware Training
by: Ashkboos, Saleh, et al.
Published: (2024)
by: Ashkboos, Saleh, et al.
Published: (2024)
Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization
by: Egiazarian, Vage, et al.
Published: (2025)
by: Egiazarian, Vage, et al.
Published: (2025)
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
by: Chen, Jiale, et al.
Published: (2025)
by: Chen, Jiale, et al.
Published: (2025)
CAGE: Curvature-Aware Gradient Estimation For Accurate Quantization-Aware Training
by: Tabesh, Soroush, et al.
Published: (2025)
by: Tabesh, Soroush, et al.
Published: (2025)
The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm
by: Chen, Jiale, et al.
Published: (2025)
by: Chen, Jiale, et al.
Published: (2025)
Grid Games: The Power of Multiple Grids for Quantizing Large Language Models
by: Egiazarian, Vage, et al.
Published: (2026)
by: Egiazarian, Vage, et al.
Published: (2026)
Towards Robust Scaling Laws for Optimizers
by: Volkova, Alexandra, et al.
Published: (2026)
by: Volkova, Alexandra, et al.
Published: (2026)
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
by: Ashkboos, Saleh, et al.
Published: (2024)
by: Ashkboos, Saleh, et al.
Published: (2024)
MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models
by: Frantar, Elias, et al.
Published: (2024)
by: Frantar, Elias, et al.
Published: (2024)
Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization
by: Nrusimha, Aniruddha, et al.
Published: (2024)
by: Nrusimha, Aniruddha, et al.
Published: (2024)
Quartet: Native FP4 Training Can Be Optimal for Large Language Models
by: Castro, Roberto L., et al.
Published: (2025)
by: Castro, Roberto L., et al.
Published: (2025)
Statistically-Lossless Quantization of Large Language Models
by: Helcig, Michael, et al.
Published: (2026)
by: Helcig, Michael, et al.
Published: (2026)
MatGPTQ: Accurate and Efficient Post-Training Matryoshka Quantization
by: Kleinegger, Maximilian, et al.
Published: (2026)
by: Kleinegger, Maximilian, et al.
Published: (2026)
Taming Unbalanced Training Workloads in Deep Learning with Partial Collective Operations
by: Li, Shigang, et al.
Published: (2019)
by: Li, Shigang, et al.
Published: (2019)
Apertus LLM Family Expansion via Distillation and Quantization
by: Panferov, Andrei, et al.
Published: (2026)
by: Panferov, Andrei, et al.
Published: (2026)
Unified Scaling Laws for Compressed Representations
by: Panferov, Andrei, et al.
Published: (2025)
by: Panferov, Andrei, et al.
Published: (2025)
Breaking (Global) Barriers in Parallel Stochastic Optimization with Wait-Avoiding Group Averaging
by: Li, Shigang, et al.
Published: (2020)
by: Li, Shigang, et al.
Published: (2020)
Behemoth: Benchmarking Unlearning in LLMs Using Fully Synthetic Data
by: Iofinova, Eugenia, et al.
Published: (2026)
by: Iofinova, Eugenia, et al.
Published: (2026)
Model Compression with Exact Budget Constraints via Riemannian Manifolds
by: Helcig, Michael, et al.
Published: (2026)
by: Helcig, Michael, et al.
Published: (2026)
Compression Scaling Laws:Unifying Sparsity and Quantization
by: Frantar, Elias, et al.
Published: (2025)
by: Frantar, Elias, et al.
Published: (2025)
ECO: Quantized Training without Full-Precision Master Weights
by: Nikdan, Mahdi, et al.
Published: (2026)
by: Nikdan, Mahdi, et al.
Published: (2026)
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
by: Malinovskii, Vladimir, et al.
Published: (2024)
by: Malinovskii, Vladimir, et al.
Published: (2024)
"Give Me BF16 or Give Me Death"? Accuracy-Performance Trade-Offs in LLM Quantization
by: Kurtic, Eldar, et al.
Published: (2024)
by: Kurtic, Eldar, et al.
Published: (2024)
Extreme Compression of Large Language Models via Additive Quantization
by: Egiazarian, Vage, et al.
Published: (2024)
by: Egiazarian, Vage, et al.
Published: (2024)
EntryPrune: Neural Network Feature Selection using First Impressions
by: Zimmer, Felix, et al.
Published: (2024)
by: Zimmer, Felix, et al.
Published: (2024)
Layer-wise Quantization for Quantized Optimistic Dual Averaging
by: Nguyen, Anh Duc, et al.
Published: (2025)
by: Nguyen, Anh Duc, et al.
Published: (2025)
LLMQ: Efficient Lower-Precision Pretraining for Consumer GPUs
by: Schultheis, Erik, et al.
Published: (2025)
by: Schultheis, Erik, et al.
Published: (2025)
Powerset Convolutional Neural Networks
by: Wendler, Chris, et al.
Published: (2019)
by: Wendler, Chris, et al.
Published: (2019)
Confounder Detection via Treatment Intent: A New Observational Study Design
by: Plecko, Drago, et al.
Published: (2026)
by: Plecko, Drago, et al.
Published: (2026)
Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence
by: Ansaripour, Matin, et al.
Published: (2022)
by: Ansaripour, Matin, et al.
Published: (2022)
LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics
by: Robert, Thomas, et al.
Published: (2024)
by: Robert, Thomas, et al.
Published: (2024)
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
by: Shutova, Alina, et al.
Published: (2025)
by: Shutova, Alina, et al.
Published: (2025)
Simple Opinion Dynamics for No-Regret Learning
by: Lazarsfeld, John, et al.
Published: (2023)
by: Lazarsfeld, John, et al.
Published: (2023)
Computational Bottlenecks of Training Small-scale Large Language Models
by: Ashkboos, Saleh, et al.
Published: (2024)
by: Ashkboos, Saleh, et al.
Published: (2024)
GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
by: Dadgarnia, Alireza, et al.
Published: (2026)
by: Dadgarnia, Alireza, et al.
Published: (2026)
Scaling Laws of Global Weather Models
by: Yu, Yuejiang, et al.
Published: (2026)
by: Yu, Yuejiang, et al.
Published: (2026)
Near-Optimal Sparse Allreduce for Distributed Deep Learning
by: Li, Shigang, et al.
Published: (2022)
by: Li, Shigang, et al.
Published: (2022)
Chimera: Efficiently Training Large-Scale Neural Networks with Bidirectional Pipelines
by: Li, Shigang, et al.
Published: (2021)
by: Li, Shigang, et al.
Published: (2021)
Similar Items
-
HALO: Hadamard-Assisted Lower-Precision Optimization for LLMs
by: Ashkboos, Saleh, et al.
Published: (2025) -
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
by: Ashkboos, Saleh, et al.
Published: (2024) -
EfQAT: An Efficient Framework for Quantization-Aware Training
by: Ashkboos, Saleh, et al.
Published: (2024) -
Bridging the Gap Between Promise and Performance for Microscaling FP4 Quantization
by: Egiazarian, Vage, et al.
Published: (2025) -
WUSH: Near-Optimal Adaptive Transforms for LLM Quantization
by: Chen, Jiale, et al.
Published: (2025)