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Data Free Quantization
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Data Free Quantization is a technique to achieve a highly accurate quantized model without accessing any training data.
Source: Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
OuroMamba: A Data-Free Quantization Framework for Vision Mamba Models
Semantics Prompting Data-Free Quantization for Low-Bit Vision Transformers
Relation-Guided Adversarial Learning for Data-free Knowledge Transfer
A method of using RSVD in residual calculation of LowBit GEMM
Privacy-Preserving SAM Quantization for Efficient Edge Intelligence in Healthcare
MimiQ: Low-Bit Data-Free Quantization of Vision Transformers with Encouraging Inter-Head Attention Similarity
EasyQuant: An Efficient Data-free Quantization Algorithm for LLMs
Robustness-Guided Image Synthesis for Data-Free Quantization
Causal-DFQ: Causality Guided Data-free Network Quantization
Data-Free Quantization via Mixed-Precision Compensation without Fine-Tuning
QNNRepair: Quantized Neural Network Repair
Towards Accurate Post-training Quantization for Diffusion Models
LLM-QAT: Data-Free Quantization Aware Training for Large Language Models
Adaptive Data-Free Quantization
Rethinking Data-Free Quantization as a Zero-Sum Game
ACQ: Improving Generative Data-free Quantization Via Attention Correction
Genie: Show Me the Data for Quantization
Zero-Shot Learning of a Conditional Generative Adversarial Network for Data-Free Network Quantization
PSAQ-ViT V2: Towards Accurate and General Data-Free Quantization for Vision Transformers
Towards Feature Distribution Alignment and Diversity Enhancement for Data-Free Quantization
Data-Free Quantization with Accurate Activation Clipping and Adaptive Batch Normalization
It's All In the Teacher: Zero-Shot Quantization Brought Closer to the Teacher
SPIQ: Data-Free Per-Channel Static Input Quantization
Patch Similarity Aware Data-Free Quantization for Vision Transformers
SQuant: On-the-Fly Data-Free Quantization via Diagonal Hessian Approximation
Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
Diverse Sample Generation: Pushing the Limit of Generative Data-free Quantization
Zero-shot Adversarial Quantization
Diversifying Sample Generation for Accurate Data-Free Quantization
Generative Zero-shot Network Quantization
Towards Accurate Quantization and Pruning via Data-free Knowledge Transfer
Generative Low-bitwidth Data Free Quantization
ZeroQ: A Novel Zero Shot Quantization Framework
Data-Free Quantization Through Weight Equalization and Bias Correction
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