Low-Bit Quantization

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21 papers in the last four weeks, up 62% on the four weeks before. 0.2% of all new papers.

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It Takes Few to TANGO: A Quantized Distributed Model for Binaural Speech Enhancement
Jul 9, 2026Zahra Benslimane, Pierre Chouteau, Martyna Poreba +4Quantization-Aware Training Speech Enhancement
Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France · Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France
BiSCo-LLM: Lookup-Free Binary Spherical Coding for Extreme Low-Bit Large Language Model Compression
Jul 9, 2026Yuantian Shao, Peisong Wang, Zhilei Liu +6LLM Compression Weight-Only Quantization
Nanjing University of Science and Technology, Nanjing, China · Institute of Automation, Chinese Academy of Sciences, Beijing, China · Huawei, China
The Silent Freeze: Predicting When Low-Precision Training Stops Learning
Jul 9, 2026Zekai ShangNeural Network Training Dynamics Low-Bit Quantization
University of Illinois at Urbana-Champaign, Champaign, IL, USA
GeoFP8: Geometry-Aware FP8 Gradient Compression for Distributed LLM Training
Jul 8, 2026Jieying Wang, Zizhong Wang, Fangru Linghu +3Language Model Pretraining Communication-Efficient Distributed Training
Department of Computer Science, Rutgers University, Piscataway, NJ, USA · Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, USA
FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models
Jul 7, 2026Bowen Xue, Zihan Min, Xingyang Li +8Diffusion Model Quantization Quantization-Aware Training
Nunchux AI · MIT · Stanford +2
Lyapunov-Guided Training for Hardware-Safe Neural Networks Under Fixed-Point Arithmetic
Jul 5, 2026Anis Hamadouche, Amir HussainLyapunov-Based Control Quantization-Aware Training
The School of Engineering & Physical Sciences Heriot-Watt University Edinburgh EH14 4AS, UK · SDAIA-KFUPM Joint Research Centre for Artificial Intelligence King Fahd University of Petroleum and Minerals Dhahran, Saudi Arabia
Variable Bit-width Quantization: Learning Per-Group Precision for "Bigger-but-Smaller" Language Models
Jul 3, 2026Hamish OgilvyMixed-Precision Quantization LLM Quantization
Algolia Research
$\text{Log}_\text{b}$ Quant: Quantizing Language Models in Logarithmic Space
Jul 1, 2026Jeremias Bohn, Tizian Dippold, Mahdi Koubaa +2LLM Quantization 4-Bit Quantization
School of Computation, Information and Technology, Technical University of Munich, Munich, Germany
GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache
Jul 1, 2026Soosung Kim, Minjae Park, Eui-Young Chung +1LLM Compression Residual VQ
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea · Department of Systems Semiconductor Engineering, Yonsei University, Seoul, Republic of Korea
Zero-Shot Quantization for Object Detectors using Off-the-Shelf Generative Models
Jun 30, 2026Hyunho Lee, Kyomin Hwang, Hyeonjin Kim +3Quantization-Aware Training Synthetic Data Generation
Seoul National University, Seoul, South Korea · LG Electronics, Seoul, South Korea
W4A4 Quantization for Inference on Wan2.2-I2V-A14B
Jun 28, 2026Yidong Chen, Chengyu Shi, Jiahao LiuDiffusion Model Quantization Post-Training Quantization
Tsinghua University
BitNet Text Embeddings
Jun 24, 2026Zhen Li, Xin Huang, Liang Wang +8LLM Quantization Embedding Compression
Peking University · Microsoft Research
RoPE-Aware Bit Allocation for KV-Cache Quantization
Jun 23, 2026Fengfeng Liang, Yuechen Zhang, Jiaya JiaKV Caching LLM Inference Acceleration
1Hong Kong University of Science and Technology · 2The Chinese University of Hong Kong · 3MiMo, Xiaomi Corporation
On the Expressive Power of Weight Quantization in Large Language Models
Jun 20, 2026Shao-Qun ZhangLLM Quantization Weight-Only Quantization
National Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210063, China. · School of Intelligent Science and Technology, Nanjing University, Suzhou 215163, China.
An Empirical Study of OpenPangu Quantization on Ascend NPUs
Jun 19, 2026Tong Shi, Jiacheng Wang, Hui Xie +4LLM Quantization AI Accelerator Inference
State Key Laboratory of Complex & Critical Software Environment, Beihang University · School of Artificial Intelligence, Beihang University · School of Computer Science and Engineering, Beihang University
SPARK: Spatial Policy-driven Adaptive Reinforcement learning for Knowledge distillation
Jun 13, 2026Mohamed Jismy Aashik Rasool, Shabir Ahmad, Gisong Oh +1Quantization-Aware Training Image Restoration
Department of IT Convergence Engineering, Gachon University, Sujeong-gu, Seongnam-si, Gyeonggi-do 461-701, Republic of Korea
Signed Symmetric Quantization for Few-Bit Integers
Jun 12, 2026Ian Colbert, Eashan Dash, Pablo Monteagudo-Lago +5LLM Quantization Weight-Only Quantization
AMD
Efficiency-Performance Trade-offs in Neural Speaker Diarization via Structured Pruning and Low-Bit Quantization
Jun 12, 2026Rishit Chatterjee, Tahiya ChowdhuryModel Compression Speaker Diarization
Department of Computer Science, Colby College, Waterville, Maine, United States
Quantum Reservoir Computing for Short-Term Power Load Forecasting in Resource-Constrained Energy Systems
Jun 11, 2026Mansi Od, Param Pathak, Nouhaila Innan +1Time Series Forecasting Reservoir Computing
University of Greenwich, London, United Kingdom · Fractal Analytics, QuantumAI Lab, Mumbai, Maharashtra, India · eBRAIN Lab, Division of Engineering, New York University Abu Dhabi (NYUAD), Abu Dhabi, UAE +1
What Limits Does Quantization Place on Dense Top- $k$ Retrieval? A Theoretical Study
Jun 10, 2026Koki Okajima, Tsukasa YoshidaInformation Retrieval Low-Bit Quantization
NTT, Inc.
Optimal Post-Training Quantization Scales and Where to Find Them
Jun 9, 2026Juan Amboage, Pablo Monteagudo-Lago, Ian Colbert +2LLM Quantization Weight-Only Quantization
AMD
UniSVQ: 2-bit Unified Scalar-Vector Quantization
Jun 9, 2026Haoyu Wang, Haiyan Zhao, Xingyu Yu +4LLM Quantization Vector Quantization
Department of Computer Science and Technology, Tsinghua University, Beijing, China · School of Software and Microelectronics, Peking University, Beijing, China · School of Physics, Beihang University, Beijing, China
Understanding Quantization-Aware Training: Gradients at Quantized Weights Bias to the Low-Loss Basin
Jun 8, 2026Hanyang Li, Jianhao Ma, Ying CuiQuantization-Aware Training Neural Network Optimization
Department of IEOR, University of California, Berkeley · Department of Statistics and Data Science, University of Pennsylvania
On Low-Bit Quantization Errors in Speaker Verification: Diagnostic and Mitigation
Jun 6, 2026Hugo Leguillier, Driss Matrouf, Guillaume Lechien +1Mixed-Precision Quantization Adaptive Inference
Avignon University, LIA, UPR 4128, France · Aday, France
OffQ: Taming Structured Outliers in LLM Quantization by Offsetting
Jun 5, 2026Haoqi Wang, Lorenz K. Mueller, Jiawei Zhuang +2LLM Quantization 4-Bit Quantization
School of Computer and Communication Sciences, EPFL, Switzerland · 2Huawei, Switzerland · 3Swiss Data Science Center, ETHZ & EPFL, Switzerland
SPEAR: A System for Post-Quantization Error-Adaptive Recovery Enabling Efficient Low-Bit LLM Serving
Jun 4, 2026Hongyuan Liu, Yawei Li, Zhiqiang Que +3LLM Quantization LLM Serving
University of Electronic Science and Technology of China · University of Bristol · 3ETH Zurich
Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models
Jun 3, 2026Rayyan Abdalla, Amir Hussein, Min Wu +1LLM Quantization LLM Inference Acceleration
Toward Multi-Domain and Long-Tailed Quantization via Feature Alignment and Scaling
Jun 3, 2026Ting-An Chen, Chin-Yuan Yeh, De-Nian YangLong-Tail Learning Low-Bit Quantization
Graduate Institute of Electrical Engineering, National Taiwan University, Taiwan · Institute of Information Science, Academia Sinica, Taiwan · Graduate Institute of Communication Engineering, National Taiwan University, Taiwan +1
Recover-LoRA for Aggressive Quantization: Reclaiming Accuracy in 2-Bit Language Models via Low-Rank Adaptation with Knowledge Distillation on Synthetic Data
Jun 2, 2026Devleena Das, Rajeev Patwari, Elliott Delaye +1Mixed-Precision Quantization LLM Quantization
Advanced Micro Devices, Inc. (AMD)
dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats
Jun 2, 2026Giuseppe Franco, Ian Colbert, Pablo Monteagudo-Lago +2Mixed-Precision Quantization LLM Quantization
AMD

Jul 9, 2026, cs.SDJ/K move · Enter open · S save

It Takes Few to TANGO: A Quantized Distributed Model for Binaural Speech Enhancement

Zahra Benslimane, Pierre Chouteau, Martyna Poreba, Fabrice Auzanneau+3

Université Paris-Saclay, CEA, List, F-91120 Palaiseau, France · Université de Lorraine, CNRS, Inria, LORIA, F-54000 Nancy, France

Quantization-Aware Training Speech Enhancement Post-Training Quantization Low-Bit Quantization Neural Network Quantization Neural Network Compression

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Neural network-based multichannel speech enhancement systems achieve strong enhancement performance, but their computational and memory requirements limit deployment on resource-constrained devices. This paper investigates low-precision inference for TANGO, a hybrid distributed binaural speech enhancement system combining neural mask estimation with spatial filtering. We evaluate post-training quantization and quantization-aware training for the neural components, and analyze how quantization errors in the mask estimators propagate through the downstream spatial filtering stage. Our analysis shows that, although quantization degrades intermediate mask estimates, the spatial filtering stage compensates for most quantization-induced errors. Leveraging this robustness, we simplify TANGO into MN-TANGO, reducing both model size and computational complexity while maintaining comparable final performance. By combining INT8 weight-and-activation quantization with ERB compression and grouped recurrent layers, the most compact MN-TANGO reaches 4.65 MMAC/s and 0.177 MB.

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Latest papers 155