Cover Image

Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Tianao, Li, Zhiteng, Yan, Xianglong, Qin, Haotong, Guo, Yong, Zhang, Yulun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

D$^2$Quant: Accurate Low-bit Post-Training Weight Quantization for LLMs
by: Yan, Xianglong, et al.
Published: (2026)

PT$^2$-LLM: Post-Training Ternarization for Large Language Models
by: Yan, Xianglong, et al.
Published: (2025)

ReCalKV: Low-Rank KV Cache Compression via Head Reordering and Offline Calibration
by: Yan, Xianglong, et al.
Published: (2025)

Progressive Binarization with Semi-Structured Pruning for LLMs
by: Yan, Xianglong, et al.
Published: (2025)

ARB-LLM: Alternating Refined Binarizations for Large Language Models
by: Li, Zhiteng, et al.
Published: (2024)

QuantVSR: Low-Bit Post-Training Quantization for Real-World Video Super-Resolution
by: Chai, Bowen, et al.
Published: (2025)

CondiQuant: Condition Number Based Low-Bit Quantization for Image Super-Resolution
by: Liu, Kai, et al.
Published: (2025)

2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution
by: Liu, Kai, et al.
Published: (2024)

Low-bit Model Quantization for Deep Neural Networks: A Survey
by: Liu, Kai, et al.
Published: (2025)

Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
by: Zhong, Yi, et al.
Published: (2026)

DVD-Quant: Data-free Video Diffusion Transformers Quantization
by: Li, Zhiteng, et al.
Published: (2025)

dLLM: Simple Diffusion Language Modeling
by: Zhou, Zhanhui, et al.
Published: (2026)

dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
by: Liu, Zhiyuan, et al.
Published: (2025)

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks
by: Qin, Haotong, et al.
Published: (2026)

BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
by: Huang, Wei, et al.
Published: (2024)

PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models
by: Zhao, Jiaqi, et al.
Published: (2025)

CrossQuant: A Post-Training Quantization Method with Smaller Quantization Kernel for Precise Large Language Model Compression
by: Liu, Wenyuan, et al.
Published: (2024)

VEQ: Modality-Adaptive Quantization for MoE Vision-Language Models
by: Qin, Guangshuo, et al.
Published: (2026)

AdaSVD: Adaptive Singular Value Decomposition for Large Language Models
by: Li, Zhiteng, et al.
Published: (2025)

ES-dLLM: Efficient Inference for Diffusion Large Language Models by Early-Skipping
by: Zhu, Zijian, et al.
Published: (2026)

InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization
by: Li, Ke, et al.
Published: (2026)

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models
by: Liu, Yifei, et al.
Published: (2024)

SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
by: Xiao, Guangxuan, et al.
Published: (2022)

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
by: Cheng, Wenhua, et al.
Published: (2025)

On-Chip Hardware-Aware Quantization for Mixed Precision Neural Networks
by: Huang, Wei, et al.
Published: (2023)

MEC-Quant: Maximum Entropy Coding for Extremely Low Bit Quantization-Aware Training
by: Pang, Junbiao, et al.
Published: (2025)

PassionSR: Post-Training Quantization with Adaptive Scale in One-Step Diffusion based Image Super-Resolution
by: Zhu, Libo, et al.
Published: (2024)

Post-Training Quantization for Video Matting
by: Zhu, Tianrui, et al.
Published: (2025)

SOAR: Scale Optimization for Accurate Reconstruction in NVFP4 Quantization
by: Bao, Chengzhu, et al.
Published: (2026)

BiDM: Pushing the Limit of Quantization for Diffusion Models
by: Zheng, Xingyu, et al.
Published: (2024)

$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
by: Du, Zhenbang, et al.
Published: (2026)

SplitQuant: Layer Splitting for Low-Bit Neural Network Quantization
by: Song, Jaewoo, et al.
Published: (2025)

Streaming-dLLM: Accelerating Diffusion LLMs via Suffix Pruning and Dynamic Decoding
by: Xiao, Zhongyu, et al.
Published: (2026)

SliderQuant: Accurate Post-Training Quantization for LLMs
by: Wang, Shigeng, et al.
Published: (2026)

QuantFace: Efficient Quantization for Face Restoration
by: Li, Jiatong, et al.
Published: (2025)

Collaborative Few-Step Distillation and Low-Bit Quantization for Wan2.2 Dual-Expert Video Diffusion Models
by: Du, Jinyang, et al.
Published: (2026)

MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
by: Feng, Weilun, et al.
Published: (2024)

First-Order Error Matters: Accurate Compensation for Quantized Large Language Models
by: Zheng, Xingyu, et al.
Published: (2025)

QuantSparse: Comprehensively Compressing Video Diffusion Transformer with Model Quantization and Attention Sparsification
by: Feng, Weilun, et al.
Published: (2025)

SplitQuantV2: Enhancing Low-Bit Quantization of LLMs Without GPUs
by: Song, Jaewoo, et al.
Published: (2025)