Cover Image

JacQuant: STE-Free Quantization-Aware Training via Learned Jacobian Surrogates

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yi, Kai, Vivekraja, Vignesh, Khaitan, Harshit, Li, Steven
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026)

JacNet: Learning Functions with Structured Jacobians
by: Lorraine, Jonathan, et al.
Published: (2024)

CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill
by: McDanel, Bradley, et al.
Published: (2026)

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference
by: Zhang, Zhenyu, et al.
Published: (2025)

MoE-Spec: Expert Budgeting for Efficient Speculative Decoding
by: McDanel, Bradley, et al.
Published: (2026)

pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware Training
by: Zhang, Wenzheng, et al.
Published: (2026)

Layerwise Progressive Freezing Enables STE-Free Training of Deep Binary Neural Networks
by: Smith, Evan Gibson, et al.
Published: (2026)

RepQuant: Towards Accurate Post-Training Quantization of Large Transformer Models via Scale Reparameterization
by: Li, Zhikai, et al.
Published: (2024)

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
by: Wei, Quan, et al.
Published: (2025)

QuantVLA: Scale-Calibrated Post-Training Quantization for Vision-Language-Action Models
by: Zhang, Jingxuan, et al.
Published: (2026)

NestQuant: Post-Training Integer-Nesting Quantization for On-Device DNN
by: Xie, Jianhang, et al.
Published: (2025)

EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
by: Tang, Hanlin, et al.
Published: (2024)

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

QuantMoE-Bench: Examining Post-Training Quantization for Mixture-of-Experts
by: Li, Pingzhi, et al.
Published: (2024)

SigmaQuant: Hardware-Aware Heterogeneous Quantization Method for Edge DNN Inference
by: Liu, Qunyou, et al.
Published: (2026)

FlatQuant: Flatness Matters for LLM Quantization
by: Sun, Yuxuan, et al.
Published: (2024)

AffineQuant: Affine Transformation Quantization for Large Language Models
by: Ma, Yuexiao, et al.
Published: (2024)

FrameQuant: Flexible Low-Bit Quantization for Transformers
by: Adepu, Harshavardhan, et al.
Published: (2024)

PrefixQuant: Eliminating Outliers by Prefixed Tokens for Large Language Models Quantization
by: Chen, Mengzhao, et al.
Published: (2024)

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

FairQuant: Fairness-Aware Mixed-Precision Quantization for Medical Image Classification
by: Woergaard, Thomas, et al.
Published: (2026)

Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models
by: Zhang, Tianao, et al.
Published: (2025)

GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
by: Kim, Jinuk, 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)

Training Implicit Networks for Image Deblurring using Jacobian-Free Backpropagation
by: Liu, Linghai, et al.
Published: (2024)

LLMEasyQuant: Scalable Quantization for Parallel and Distributed LLM Inference
by: Liu, Dong, et al.
Published: (2024)

GoQuant: Geometric Orthogonal Residual Projection for Multiplier-Free Power-of-Two Transformer Quantization
by: Xiang, Maoyang, et al.
Published: (2026)

Counterfactual Reward Model Training for Bias Mitigation in Multimodal Reinforcement Learning
by: Mathew, Sheryl, et al.
Published: (2025)

QuantLRM: Quantization of Large Reasoning Models via Fine-Tuning Signals
by: Zhang, Nan, et al.
Published: (2026)

PolarQuant: Quantizing KV Caches with Polar Transformation
by: Han, Insu, et al.
Published: (2025)

OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
by: Shao, Wenqi, et al.
Published: (2023)

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization
by: Xi, Haocheng, et al.
Published: (2026)

QuantKAN: A Unified Quantization Framework for Kolmogorov Arnold Networks
by: Fuad, Kazi Ahmed Asif, et al.
Published: (2025)

Jacobian-Enhanced Neural Networks
by: Berguin, Steven H.
Published: (2024)

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

PolarQuant: Optimal Gaussian Weight Quantization via Hadamard Rotation for LLM Compression
by: Vicentino, Caio
Published: (2026)

DartQuant: Efficient Rotational Distribution Calibration for LLM Quantization
by: Shao, Yuantian, et al.
Published: (2025)

NanoQuant: Efficient Sub-1-Bit Quantization of Large Language Models
by: Chong, Hyochan, et al.
Published: (2026)

TruncQuant: Truncation-Ready Quantization for DNNs with Flexible Weight Bit Precision
by: Kim, Jinhee, et al.
Published: (2025)

End-to-End Training of High-Dimensional Optimal Control with Implicit Hamiltonians via Jacobian-Free Backpropagation
by: Gelphman, Eric, et al.
Published: (2025)