A Survey of Quantization Methods for Efficient Neural Network Inference | Paper Citation Record

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LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale cites this paper.

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 135

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GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers cites this paper.

GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 6

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AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration cites this paper.

AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 16

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Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity cites this paper.

Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 12

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Column-wise Quantization of Weights and Partial Sums for Accurate and Efficient Compute-In-Memory Accelerators cites this paper.

Column-wise Quantization of Weights and Partial Sums for Accurate and Efficient Compute-In-Memory Accelerators A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 12

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Setup Once, Secure Always: A Single-Setup Secure Federated Learning Aggregation Protocol with Forward and Backward Secrecy for Dynamic Users cites this paper.

Setup Once, Secure Always: A Single-Setup Secure Federated Learning Aggregation Protocol with Forward and Backward Secrecy for Dynamic Users A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 14

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When Do Neural Networks Learn World Models? cites this paper.

When Do Neural Networks Learn World Models? A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 27

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Can Post-Training Quantization Benefit from an Additional QLoRA Integration? cites this paper.

Can Post-Training Quantization Benefit from an Additional QLoRA Integration? A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 10

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Forget the Data and Fine-Tuning! Just Fold the Network to Compress cites this paper.

Forget the Data and Fine-Tuning! Just Fold the Network to Compress A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 24

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Is (Selective) Round-To-Nearest Quantization All You Need? cites this paper.

Is (Selective) Round-To-Nearest Quantization All You Need? A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2021

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Large Language Model Meets Constraint Propagation cites this paper.

Large Language Model Meets Constraint Propagation A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 29

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BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing cites this paper.

BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 18

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QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference cites this paper.

QPART: Adaptive Model Quantization and Dynamic Workload Balancing for Accuracy-aware Edge Inference A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 55

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TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents cites this paper.

TD-MPC-Opt: Distilling Model-Based Multi-Task Reinforcement Learning Agents A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 8

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Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications cites this paper.

Design of an Edge-based Portable EHR System for Anemia Screening in Remote Health Applications A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 29

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Performance Analysis of Post-Training Quantization for CNN-based Conjunctival Pallor Anemia Detection cites this paper.

Performance Analysis of Post-Training Quantization for CNN-based Conjunctival Pallor Anemia Detection A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 11

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The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm cites this paper.

The Geometry of LLM Quantization: GPTQ as Babai's Nearest Plane Algorithm A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 6

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LCS: An AI-based Low-Complexity Scaler for Power-Efficient Super-Resolution of Game Content cites this paper.

LCS: An AI-based Low-Complexity Scaler for Power-Efficient Super-Resolution of Game Content A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 9

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DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling cites this paper.

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 18

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Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems cites this paper.

Hardware Acceleration of Kolmogorov-Arnold Network (KAN) in Large-Scale Systems A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 19

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SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models cites this paper.

SQAP-VLA: A Synergistic Quantization-Aware Pruning Framework for High-Performance Vision-Language-Action Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2021

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You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 20

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You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations cites this paper.

You Had One Job: Per-Task Quantization Using LLMs' Hidden Representations A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 20

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MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM cites this paper.

MoBiQuant: Mixture-of-Bits Quantization for Token-Adaptive Any-Precision LLM A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2024

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No Certificate, No Categorical Speech Act: A Brouwerian Assertibility Constraint for Public Reason cites this paper.

No Certificate, No Categorical Speech Act: A Brouwerian Assertibility Constraint for Public Reason A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 32

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PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation cites this paper.

PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 57

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Sustainability Is Not Linear: Quantifying Performance, Energy, and Privacy Trade-offs in On-Device Intelligence cites this paper.

Sustainability Is Not Linear: Quantifying Performance, Energy, and Privacy Trade-offs in On-Device Intelligence A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 59

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Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization cites this paper.

Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 12

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Harnessing Photonics for Machine Intelligence cites this paper.

Harnessing Photonics for Machine Intelligence A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 24

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Litespark Inference For CPUs: Ultra-Fast SIMD Framework for Ternary (1.58-bit) Language Models cites this paper.

Litespark Inference For CPUs: Ultra-Fast SIMD Framework for Ternary (1.58-bit) Language Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 15

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Litespark Inference For CPUs: Ultra-Fast SIMD Framework for Ternary (1.58-bit) Language Models cites this paper.

Litespark Inference For CPUs: Ultra-Fast SIMD Framework for Ternary (1.58-bit) Language Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 15

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LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 34

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LoKA: Low-precision Kernel Applications for Recommendation Models At Scale cites this paper.

LoKA: Low-precision Kernel Applications for Recommendation Models At Scale A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 34

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Rethink the Role of Neural Decoders in Quantum Error Correction cites this paper.

Rethink the Role of Neural Decoders in Quantum Error Correction A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 12

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Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap cites this paper.

Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 106

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Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis cites this paper.

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 297

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When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 11

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When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 11

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When Bits Break Recourse: Counterfactual-Faithful Quantization cites this paper.

When Bits Break Recourse: Counterfactual-Faithful Quantization A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 11

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Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation cites this paper.

Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 3

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The Thermodynamic Costs of Simple Linear Regression cites this paper.

The Thermodynamic Costs of Simple Linear Regression A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 77

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K-Quantization and its Impact on Output Performance cites this paper.

K-Quantization and its Impact on Output Performance A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 53

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Machine learning enables experimental access to photon-by-photon arrival times in scintillation detectors cites this paper.

Machine learning enables experimental access to photon-by-photon arrival times in scintillation detectors A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 53

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The Complexity of Verifying Feedforward Neural Networks in Quantised Settings cites this paper.

The Complexity of Verifying Feedforward Neural Networks in Quantised Settings A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 5

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PALUTE: Processing-In-Memory Acceleration via Lookup Table for Edge LLM Inference cites this paper.

PALUTE: Processing-In-Memory Acceleration via Lookup Table for Edge LLM Inference A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 10

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Minimum Distortion Quantization with Specified Output Distribution cites this paper.

Minimum Distortion Quantization with Specified Output Distribution A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 16

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Quantizing Time-Series Models As Dynamical Systems: Trajectory-Based Quantization Sensitivity Score cites this paper.

Quantizing Time-Series Models As Dynamical Systems: Trajectory-Based Quantization Sensitivity Score A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 34

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On the Expressive Power of Weight Quantization in Large Language Models cites this paper.

On the Expressive Power of Weight Quantization in Large Language Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 15

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Observation e5514e51-a7fd-494b-9431-cf45e6db27f9 · inbound

SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference cites this paper.

SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 124

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Observation cfe547c6-22bf-441d-a7c8-09ba03676a89 · inbound

Quantization in Federated Learning: Methods, Challenges and Future Directions cites this paper.

Quantization in Federated Learning: Methods, Challenges and Future Directions A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 38

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Observation f5d6647f-9421-400f-aee8-8bac83eb7ee4 · inbound

$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic Space cites this paper.

$\text{Log}_\text{b}$Quant: Quantizing Language Models in Logarithmic Space A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 15

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Observation 4159fcf2-36dd-47b0-80b2-a690665a03d8 · inbound

Lyapunov-Guided Training for Hardware-Safe Neural Networks Under Fixed-Point Arithmetic cites this paper.

Lyapunov-Guided Training for Hardware-Safe Neural Networks Under Fixed-Point Arithmetic A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 8

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ExaGEMM: Exploration Framework for CPU-Driven ML Inference via Associative In-Register Computing for Low-Bit GEMM cites this paper.

ExaGEMM: Exploration Framework for CPU-Driven ML Inference via Associative In-Register Computing for Low-Bit GEMM A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T01:37:47.281341Z

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QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs cites this paper.

QScheduler: Adaptive Gradient Sampling for Zeroth-Order On-Device Training on INT8 NPUs A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T14:20:27.328655Z

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Observation 9d56633a-8464-4bf9-b762-95bb344dd067 · inbound

Lightweight Image Classification of Raptor Species for Edge Devices: Rare-Species Dataset Expansion via Video Frame Extraction, Knowledge Distillation, and TensorRT Deployment cites this paper.

Lightweight Image Classification of Raptor Species for Edge Devices: Rare-Species Dataset Expansion via Video Frame Extraction, Knowledge Distillation, and TensorRT Deployment A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T00:28:14.757587Z

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Observation 824d8568-6119-4bcc-91c5-30e341240d80 · inbound

MixFrag: Fragility-Guided Mixed-Precision Post-Training Quantization for Vision Transformers cites this paper.

MixFrag: Fragility-Guided Mixed-Precision Post-Training Quantization for Vision Transformers A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T02:57:27.356357Z

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Observation 04db17ea-4882-4970-9c26-d5fb26d0e2c5 · inbound

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models cites this paper.

TASQ: Temporal-Adaptive Bit Sparsification Quantization for Diffusion Models A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T01:04:45.725654Z

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