SOTAVerified

Quantization

Quantization is a promising technique to reduce the computation cost of neural network training, which can replace high-cost floating-point numbers (e.g., float32) with low-cost fixed-point numbers (e.g., int8/int16).

Source: Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers

Papers

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Showing 501–550 of 4925 papers

TitleStatusHype
Survey of Quantization Techniques for On-Device Vision-based Crack Detection—0
Unlocking Efficient Large Inference Models: One-Bit Unrolling Tips the Scales—0
Massive Values in Self-Attention Modules are the Key to Contextual Knowledge UnderstandingCode2
Choose Your Model Size: Any Compression by a Single Gradient Descent—0
QLESS: A Quantized Approach for Data Valuation and Selection in Large Language Model Fine-TuningCode0
Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis—0
An Inquiry into Datacenter TCO for LLM Inference with FP8—0
Nearly Lossless Adaptive Bit SwitchingCode0
Structural Latency Perturbation in Large Language Models Through Recursive State Induction—0
Huff-LLM: End-to-End Lossless Compression for Efficient LLM Inference—0
On Noncommutative Quantum Mechanics and the Black-Scholes Model—0
MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization—0
Enhancing Field-Oriented Control of Electric Drives with Tiny Neural Network Optimized for Micro-controllers—0
LLM-based Affective Text Generation Quality Based on Different Quantization Values—0
Visual Autoregressive Modeling for Image Super-ResolutionCode2
Fully Distributed and Quantized Algorithm for MPC-based Autonomous Vehicle Platooning Optimization—0
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language ModelsCode1
Mixed-Precision Graph Neural Quantization for Low Bit Large Language Models—0
CodeBrain: Impute Any Brain MRI via Instance-specific Scalar-quantized Codes—0
Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation—0
Post-Training Quantization for 3D Medical Image Segmentation: A Practical Study on Real Inference EnginesCode0
Post-Training Quantization for Vision Mamba with k-Scaled Quantization and Reparameterization—0
EdgeMLOps: Operationalizing ML models with Cumulocity IoT and thin-edge.io for Visual quality Inspection—0
Optimizing Large Language Model Training Using FP4 Quantization—0
Stabilization of an unstable reaction-diffusion PDE with input delay despite state and input quantization—0
One-Bit Sigma-Delta DFRC Waveform Design: Using Quantization Noise for Radar Probing—0
SQ-DM: Accelerating Diffusion Models with Aggressive Quantization and Temporal Sparsity—0
Decentralized Low-Rank Fine-Tuning of Large Language Models—0
GaussianToken: An Effective Image Tokenizer with 2D Gaussian SplattingCode2
FBQuant: FeedBack Quantization for Large Language Models—0
RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations—0
AKVQ-VL: Attention-Aware KV Cache Adaptive 2-Bit Quantization for Vision-Language Models—0
On Accelerating Edge AI: Optimizing Resource-Constrained Environments—0
SwiftPrune: Hessian-Free Weight Pruning for Large Language Models—0
Channel-Aware Constellation Design for Digital OTA Computation—0
End-to-end workflow for machine learning-based qubit readout with QICK and hls4ml—0
On Hardening DNNs against Noisy Computations—0
OstQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution FittingCode2
Qrazor: Reliable and effortless 4-bit llm quantization by significant data razoring—0
QMamba: Post-Training Quantization for Vision State Space Models—0
MambaQuant: Quantizing the Mamba Family with Variance Aligned Rotation Methods—0
Diffusion-based Perceptual Neural Video Compression with Temporal Diffusion Information Reuse—0
DQ-Data2vec: Decoupling Quantization for Multilingual Speech Recognition—0
Quantized Spike-driven TransformerCode1
HEPPO: Hardware-Efficient Proximal Policy Optimization -- A Universal Pipelined Architecture for Generalized Advantage Estimation—0
Irrational Complex Rotations Empower Low-bit Optimizers—0
Sketch and Patch: Efficient 3D Gaussian Representation for Man-Made Scenes—0
GANQ: GPU-Adaptive Non-Uniform Quantization for Large Language ModelsCode0
SplitQuant: Layer Splitting for Low-Bit Neural Network Quantization—0
HAC++: Towards 100X Compression of 3D Gaussian SplattingCode3
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All datasetsImageNetCIFAR-10Wiki-40BAgeDB-30CFP-FPCOCO (Common Objects in Context)IJB-BIJB-CKnowledge-based:LFW

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FQ-ViT (ViT-L)Top-1 Accuracy (%)85.03—Unverified
2FQ-ViT (ViT-B)Top-1 Accuracy (%)83.31—Unverified
3FQ-ViT (Swin-B)Top-1 Accuracy (%)82.97—Unverified
4FQ-ViT (Swin-S)Top-1 Accuracy (%)82.71—Unverified
5FQ-ViT (DeiT-B)Top-1 Accuracy (%)81.2—Unverified
6FQ-ViT (Swin-T)Top-1 Accuracy (%)80.51—Unverified
7FQ-ViT (DeiT-S)Top-1 Accuracy (%)79.17—Unverified
8Xception W8A8Top-1 Accuracy (%)78.97—Unverified
9ADLIK-MO-ResNet50-W4A4Top-1 Accuracy (%)77.88—Unverified
10ADLIK-MO-ResNet50-W3A4Top-1 Accuracy (%)77.34—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_3MAP160,327.04—Unverified
2DTQMAP0.79—Unverified
#ModelMetricClaimedVerifiedStatus
1OutEffHop-Bert_basePerplexity6.3—Unverified
2OutEffHop-Bert_basePerplexity6.21—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy98.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy92.92—Unverified
#ModelMetricClaimedVerifiedStatus
1SSD ResNet50 V1 FPN 640x640MAP34.3—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-495.13—Unverified
#ModelMetricClaimedVerifiedStatus
1TAR @ FAR=1e-496.38—Unverified
#ModelMetricClaimedVerifiedStatus
13DCNN_VIVA_5All84,809,664—Unverified
#ModelMetricClaimedVerifiedStatus
1Accuracy99.8—Unverified