LFQ: Logit-aware Final-block Quantization for Boosting the Generation Quality of Low-Bit Quantized LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Lee, Jung Hyun, Yang, June Yong, Choi, Jungwook, Yang, Eunho |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices
by: Lee, Jung Hyun, et al.
Published: (2024)
by: Lee, Jung Hyun, et al.
Published: (2024)
No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization
by: Yang, June Yong, et al.
Published: (2024)
by: Yang, June Yong, et al.
Published: (2024)
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
by: Park, Jiwoong, et al.
Published: (2025)
by: Park, Jiwoong, et al.
Published: (2025)
Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning
by: Li, Zhen, et al.
Published: (2025)
by: Li, Zhen, et al.
Published: (2025)
Q-Palette: Fractional-Bit Quantizers Toward Optimal Bit Allocation for Efficient LLM Deployment
by: Lee, Deokjae, et al.
Published: (2025)
by: Lee, Deokjae, et al.
Published: (2025)
Quantization Meets Reasoning: Exploring and Mitigating Degradation of Low-Bit LLMs in Mathematical Reasoning
by: Li, Zhen, et al.
Published: (2025)
by: Li, Zhen, et al.
Published: (2025)
RILQ: Rank-Insensitive LoRA-based Quantization Error Compensation for Boosting 2-bit Large Language Model Accuracy
by: Lee, Geonho, et al.
Published: (2024)
by: Lee, Geonho, et al.
Published: (2024)
LittleBit: Ultra Low-Bit Quantization via Latent Factorization
by: Lee, Banseok, et al.
Published: (2025)
by: Lee, Banseok, et al.
Published: (2025)
HESTIA: A Hessian-Guided Differentiable Quantization-Aware Training Framework for Extremely Low-Bit LLMs
by: Wang, Guoan, et al.
Published: (2026)
by: Wang, Guoan, et al.
Published: (2026)
SplitQuantV2: Enhancing Low-Bit Quantization of LLMs Without GPUs
by: Song, Jaewoo, et al.
Published: (2025)
by: Song, Jaewoo, et al.
Published: (2025)
SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization
by: Zhao, Zhixiong, et al.
Published: (2025)
by: Zhao, Zhixiong, et al.
Published: (2025)
Unleashing the Potential of Text-attributed Graphs: Automatic Relation Decomposition via Large Language Models
by: Seo, Hyunjin, et al.
Published: (2024)
by: Seo, Hyunjin, et al.
Published: (2024)
Token-Supervised Value Models for Enhancing Mathematical Problem-Solving Capabilities of Large Language Models
by: Lee, Jung Hyun, et al.
Published: (2024)
by: Lee, Jung Hyun, et al.
Published: (2024)
Q$^2$: Quantization-Aware Gradient Balancing and Attention Alignment for Low-Bit Quantization
by: Wang, Zhaoyang, et al.
Published: (2025)
by: Wang, Zhaoyang, et al.
Published: (2025)
NSNQuant: A Double Normalization Approach for Calibration-Free Low-Bit Vector Quantization of KV Cache
by: Son, Donghyun, et al.
Published: (2025)
by: Son, Donghyun, et al.
Published: (2025)
Evolution Strategy-Based Calibration for Low-Bit Quantization of Speech Models
by: Rakotoarivony, Lucas
Published: (2026)
by: Rakotoarivony, Lucas
Published: (2026)
HBLLM: Wavelet-Enhanced High-Fidelity 1-Bit Quantization for LLMs
by: Chen, Ningning, et al.
Published: (2025)
by: Chen, Ningning, et al.
Published: (2025)
MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity
by: Choi, Kanghyun, et al.
Published: (2024)
by: Choi, Kanghyun, et al.
Published: (2024)
InfoQuant: Shaping Activation Distributions for Low-Bit LLM Quantization
by: Li, Ke, et al.
Published: (2026)
by: Li, Ke, et al.
Published: (2026)
Learning Grouped Lattice Vector Quantizers for Low-Bit LLM Compression
by: Zhang, Xi, et al.
Published: (2025)
by: Zhang, Xi, et al.
Published: (2025)
Why Do Some Inputs Break Low-Bit LLM Quantization?
by: Chang, Ting-Yun, et al.
Published: (2025)
by: Chang, Ting-Yun, et al.
Published: (2025)
SplitQuant: Layer Splitting for Low-Bit Neural Network Quantization
by: Song, Jaewoo, et al.
Published: (2025)
by: Song, Jaewoo, et al.
Published: (2025)
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
by: Lee, Jung Hyun, et al.
Published: (2023)
by: Lee, Jung Hyun, et al.
Published: (2023)
Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models
by: Zhang, Tianao, et al.
Published: (2025)
by: Zhang, Tianao, et al.
Published: (2025)
Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs
by: Lee, Jung Hyun, et al.
Published: (2025)
by: Lee, Jung Hyun, et al.
Published: (2025)
What Makes Low-Bit Quantization-Aware Training Work for Reasoning LLMs? A Systematic Study
by: Lv, Keyu, et al.
Published: (2026)
by: Lv, Keyu, et al.
Published: (2026)
ECQ$^{\text{x}}$: Explainability-Driven Quantization for Low-Bit and Sparse DNNs
by: Becking, Daniel, et al.
Published: (2021)
by: Becking, Daniel, et al.
Published: (2021)
Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization
by: Luo, Róisín, et al.
Published: (2024)
by: Luo, Róisín, et al.
Published: (2024)
Collaborative Few-Step Distillation and Low-Bit Quantization for Wan2.2 Dual-Expert Video Diffusion Models
by: Du, Jinyang, et al.
Published: (2026)
by: Du, Jinyang, et al.
Published: (2026)
Progressive Fine-to-Coarse Reconstruction for Accurate Low-Bit Post-Training Quantization in Vision Transformers
by: Ding, Rui, et al.
Published: (2024)
by: Ding, Rui, et al.
Published: (2024)
SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs
by: Cheng, Wenhua, et al.
Published: (2025)
by: Cheng, Wenhua, et al.
Published: (2025)
HeRo-Q: A General Framework for Stable Low Bit Quantization via Hessian Conditioning
by: Zhang, Jinhao Zhang Yunquan, et al.
Published: (2026)
by: Zhang, Jinhao Zhang Yunquan, et al.
Published: (2026)
AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler
by: Kim, Changhun, et al.
Published: (2024)
by: Kim, Changhun, et al.
Published: (2024)
Prune-then-Quantize or Quantize-then-Prune? Understanding the Impact of Compression Order in Joint Model Compression
by: Kim, Minjun, et al.
Published: (2026)
by: Kim, Minjun, et al.
Published: (2026)
Quantized Evolution Strategies: High-precision Fine-tuning of Quantized LLMs at Low-precision Cost
by: Xu, Yinggan, et al.
Published: (2026)
by: Xu, Yinggan, et al.
Published: (2026)
I-LLM: Efficient Integer-Only Inference for Fully-Quantized Low-Bit Large Language Models
by: Hu, Xing, et al.
Published: (2024)
by: Hu, Xing, et al.
Published: (2024)
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
by: Zhong, Yi, et al.
Published: (2026)
by: Zhong, Yi, et al.
Published: (2026)
ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs
by: Meng, Haoqian, et al.
Published: (2026)
by: Meng, Haoqian, et al.
Published: (2026)
ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
by: Yin, Junjie, et al.
Published: (2023)
by: Yin, Junjie, et al.
Published: (2023)
MapCoder-Lite: Distilling Multi-Agent Coding into a Single Small LLM
by: Lee, Woongkyu, et al.
Published: (2025)
by: Lee, Woongkyu, et al.
Published: (2025)
Similar Items
-
LRQ: Optimizing Post-Training Quantization for Large Language Models by Learning Low-Rank Weight-Scaling Matrices
by: Lee, Jung Hyun, et al.
Published: (2024) -
No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization
by: Yang, June Yong, et al.
Published: (2024) -
Enhancing Generalization in Data-free Quantization via Mixup-class Prompting
by: Park, Jiwoong, et al.
Published: (2025) -
Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning
by: Li, Zhen, et al.
Published: (2025) -
Q-Palette: Fractional-Bit Quantizers Toward Optimal Bit Allocation for Efficient LLM Deployment
by: Lee, Deokjae, et al.
Published: (2025)