Diffusion Model Quantization: A Review | Paper Citation Record

Observation 313c05a4-ea13-4427-b06d-648ddbec90d9 · outbound

This paper cites Deep un- supervised learning using nonequilibrium thermodynamics.

Diffusion Model Quantization: A Review Deep un- supervised learning using nonequilibrium thermodynamics

Reference 1

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This paper cites Denoising diffusion probabilistic models.

Diffusion Model Quantization: A Review Denoising diffusion probabilistic models

Reference 2

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This paper cites Generative modeling by estimating gradients of the data distribution.

Diffusion Model Quantization: A Review Generative modeling by estimating gradients of the data distribution

Reference 3

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This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Diffusion Model Quantization: A Review Score-Based Generative Modeling through Stochastic Differential Equations

Reference 4

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This paper cites Auto-Encoding Variational Bayes.

Diffusion Model Quantization: A Review Auto-Encoding Variational Bayes

Reference 5

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This paper cites Generative adversarial network: An overview of theory and applications.

Diffusion Model Quantization: A Review Generative adversarial network: An overview of theory and applications

Reference 6

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This paper cites Conditional text image generation with diffusion models.

Diffusion Model Quantization: A Review Conditional text image generation with diffusion models

Reference 7

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This paper cites Adding conditional control to text-to- image diffusion models.

Diffusion Model Quantization: A Review Adding conditional control to text-to- image diffusion models

Reference 8

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This paper cites SinSR: Diffusion-Based Image Super-Resolution in a Single Step.

Diffusion Model Quantization: A Review SinSR: Diffusion-Based Image Super-Resolution in a Single Step

Reference 9

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This paper cites Srdiff: Single image super-resolution with diffusion probabilistic models.

Diffusion Model Quantization: A Review Srdiff: Single image super-resolution with diffusion probabilistic models

Reference 10

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This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Diffusion Model Quantization: A Review Repaint: Inpainting using denoising diffusion probabilistic models

Reference 11

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Observation da947b0e-488f-4f5c-aa87-a7c2997b8126 · outbound

This paper cites Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation.

Diffusion Model Quantization: A Review Renderdiffusion: Image diffusion for 3d reconstruction, inpainting and generation

Reference 12

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This paper cites Inversion-based style transfer with diffusion models.

Diffusion Model Quantization: A Review Inversion-based style transfer with diffusion models

Reference 13

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This paper cites Stylediffusion: Controllable disentangled style transfer via diffusion models.

Diffusion Model Quantization: A Review Stylediffusion: Controllable disentangled style transfer via diffusion models

Reference 14

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This paper cites Diffusion-enhanced patchmatch: A framework for arbitrary style transfer with diffusion models.

Diffusion Model Quantization: A Review Diffusion-enhanced patchmatch: A framework for arbitrary style transfer with diffusion models

Reference 15

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Observation ac1bf6fc-2229-48ad-bedb-9666b4df5912 · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

Diffusion Model Quantization: A Review Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 16

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This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

Diffusion Model Quantization: A Review CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 17

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This paper cites Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning.

Diffusion Model Quantization: A Review Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning

Reference 18

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This paper cites Csdi: Conditional score- based diffusion models for probabilistic time series imputation.

Diffusion Model Quantization: A Review Csdi: Conditional score- based diffusion models for probabilistic time series imputation

Reference 19

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This paper cites Generative time series forecasting with diffusion, denoise, and disentanglement.

Diffusion Model Quantization: A Review Generative time series forecasting with diffusion, denoise, and disentanglement

Reference 20

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This paper cites Proteinsgm: Score-based generative modeling for de novo protein design.

Diffusion Model Quantization: A Review Proteinsgm: Score-based generative modeling for de novo protein design

Reference 21

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Observation cbebd642-05dd-4728-bc60-0646f62b362e · outbound

This paper cites Equivariant diffusion for molecule generation in 3d.

Diffusion Model Quantization: A Review Equivariant diffusion for molecule generation in 3d

Reference 22

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Observation 3e563c84-f32b-4926-a874-1bbdaaafda62 · outbound

This paper cites High-frequency space diffusion model for accelerated mri.

Diffusion Model Quantization: A Review High-frequency space diffusion model for accelerated mri

Reference 23

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This paper cites Metal inpainting in cbct projections using score- based generative model.

Diffusion Model Quantization: A Review Metal inpainting in cbct projections using score- based generative model

Reference 24

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This paper cites High-resolution image synthesis with latent diffusion models.

Diffusion Model Quantization: A Review High-resolution image synthesis with latent diffusion models

Reference 25

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This paper cites DilateQuant: Accurate and Efficient Diffusion Quantization via Weight Dilation.

Diffusion Model Quantization: A Review DilateQuant: Accurate and Efficient Diffusion Quantization via Weight Dilation

Reference 26

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This paper cites Score-Based Generative Modeling with Critically-Damped Langevin Diffusion.

Diffusion Model Quantization: A Review Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Reference 27

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This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Diffusion Model Quantization: A Review Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 28

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Observation f0b636fa-6ca5-40f1-99c2-afc934237bea · outbound

This paper cites Pseudo Numerical Methods for Diffusion Models on Manifolds.

Diffusion Model Quantization: A Review Pseudo Numerical Methods for Diffusion Models on Manifolds

Reference 29

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This paper cites Come-closer-diffuse-faster: Accelerat- ing conditional diffusion models for inverse problems through stochastic contraction.

Diffusion Model Quantization: A Review Come-closer-diffuse-faster: Accelerat- ing conditional diffusion models for inverse problems through stochastic contraction

Reference 30

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This paper cites How much is enough? a study on diffusion times in score- based generative models.

Diffusion Model Quantization: A Review How much is enough? a study on diffusion times in score- based generative models

Reference 31

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This paper cites Instaflow: One step is enough for high-quality diffusion-based text-to-image generation.

Diffusion Model Quantization: A Review Instaflow: One step is enough for high-quality diffusion-based text-to-image generation

Reference 32

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This paper cites Variational diffusion models.

Diffusion Model Quantization: A Review Variational diffusion models

Reference 33

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This paper cites On Fast Sampling of Diffusion Probabilistic Models.

Diffusion Model Quantization: A Review On Fast Sampling of Diffusion Probabilistic Models

Reference 34

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This paper cites Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models.

Diffusion Model Quantization: A Review Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models

Reference 35

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Diffusion Model Quantization: A Review Structural pruning for diffusion models

Reference 36

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Diffusion Model Quantization: A Review LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models

Reference 37

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Diffusion Model Quantization: A Review Progressive Distillation for Fast Sampling of Diffusion Models

Reference 38

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This paper cites On distillation of guided diffusion models.

Diffusion Model Quantization: A Review On distillation of guided diffusion models

Reference 39

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Diffusion Model Quantization: A Review Post-training quantiza- tion on diffusion models

Reference 40

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This paper cites Q-diffusion: Quantizing diffusion models.

Diffusion Model Quantization: A Review Q-diffusion: Quantizing diffusion models

Reference 41

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This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Diffusion Model Quantization: A Review Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 42

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This paper cites A White Paper on Neural Network Quantization.

Diffusion Model Quantization: A Review A White Paper on Neural Network Quantization

Reference 43

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Diffusion Model Quantization: A Review Ptqd: Accurate post-training quantization for diffusion models

Reference 44

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Diffusion Model Quantization: A Review Temporal dynamic quantization for diffusion models

Reference 45

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Diffusion Model Quantization: A Review D$^2$-DPM: Dual Denoising for Quantized Diffusion Probabilistic Models

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This paper cites BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction.

Diffusion Model Quantization: A Review BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction

Reference 47

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Diffusion Model Quantization: A Review SpinQuant: LLM quantization with learned rotations

Reference 48

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This paper cites Awq: Activation-aware weight quan- tization for on-device llm compression and acceleration.

Diffusion Model Quantization: A Review Awq: Activation-aware weight quan- tization for on-device llm compression and acceleration

Reference 49

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Diffusion Model Quantization: A Review Towards accurate post-training quantization for diffusion models

Reference 51

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Diffusion Model Quantization: A Review Tfmq-dm: Tempo- ral feature maintenance quantization for diffusion models

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Diffusion Model Quantization: A Review Qvd: Post-training quantization for video diffusion models

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Diffusion Model Quantization: A Review Q-dm: An efficient low-bit quantized diffusion model

Reference 54

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Diffusion Model Quantization: A Review QuEST: Low-bit Diffusion Model Quantization via Efficient Selective Finetuning

Reference 55

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Diffusion Model Quantization: A Review Memory-efficient fine-tuning for quantized diffusion model

Reference 56

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Diffusion Model Quantization: A Review EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models

Reference 57

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Diffusion Model Quantization: A Review IntLoRA: Integral Low-rank Adaptation of Quantized Diffusion Models

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Diffusion Model Quantization: A Review Binary latent diffusion

Reference 59

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Diffusion Model Quantization: A Review Binarydm: Accurate weight binarization for efficient diffusion models

Reference 60

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Diffusion Model Quantization: A Review BiDM: Pushing the Limit of Quantization for Diffusion Models

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This paper cites BitsFusion: 1.99 bits Weight Quantization of Diffusion Model.

Diffusion Model Quantization: A Review BitsFusion: 1.99 bits Weight Quantization of Diffusion Model

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Diffusion Model Quantization: A Review Binarized Diffusion Model for Image Super-Resolution

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This paper cites Timestep-Aware Correction for Quantized Diffusion Models.

Diffusion Model Quantization: A Review Timestep-Aware Correction for Quantized Diffusion Models

Reference 64

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This paper cites Scalable diffusion models with transformers.

Diffusion Model Quantization: A Review Scalable diffusion models with transformers

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This paper cites An Analysis on Quantizing Diffusion Transformers.

Diffusion Model Quantization: A Review An Analysis on Quantizing Diffusion Transformers

Reference 66

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Diffusion Model Quantization: A Review Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers

Reference 67

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Diffusion Model Quantization: A Review PTQ4DiT: Post-training Quantization for Diffusion Transformers

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Diffusion Model Quantization: A Review DiTAS: Quantizing Diffusion Transformers via Enhanced Activation Smoothing

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This paper cites Vidit-q: Efficient and accurate quantization of diffusion transformers for image and video generation, 2024.

Diffusion Model Quantization: A Review Vidit-q: Efficient and accurate quantization of diffusion transformers for image and video generation, 2024

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Diffusion Model Quantization: A Review HQ-DiT: Efficient Diffusion Transformer with FP4 Hybrid Quantization

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Diffusion Model Quantization: A Review Quantization networks

Reference 72

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Diffusion Model Quantization: A Review Zeroquant: Efficient and affordable post-training quantization for large-scale trans- formers

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Diffusion Model Quantization: A Review Smoothquant: Accurate and efficient post-training quantization for large language models

Reference 74

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Diffusion Model Quantization: A Review Over- coming oscillations in quantization-aware training

Reference 75

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Diffusion Model Quantization: A Review Degree-Quant: Quantization-Aware Training for Graph Neural Networks

Reference 76

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Diffusion Model Quantization: A Review Make repvgg greater again: A quantization-aware approach

Reference 77

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Diffusion Model Quantization: A Review Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 78

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Diffusion Model Quantization: A Review Up or down? adaptive rounding for post-training quantization

Reference 79

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Diffusion Model Quantization: A Review Learned Step Size Quantization

Reference 80

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Diffusion Model Quantization: A Review Prequant: A task-agnostic quantization approach for pre-trained language models

Reference 81

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Diffusion Model Quantization: A Review Memory-efficient fine-tuning of compressed large language models via sub-4-bit integer quantization

Reference 82

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Diffusion Model Quantization: A Review An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 83

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Diffusion Model Quantization: A Review ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

Reference 84

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Diffusion Model Quantization: A Review Learning multiple layers of features from tiny images

Reference 85

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Diffusion Model Quantization: A Review Denoising Diffusion Implicit Models

Reference 86

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Diffusion Model Quantization: A Review Imagenet: A large- scale hierarchical image database

Reference 87

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Diffusion Model Quantization: A Review LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 88

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Diffusion Model Quantization: A Review Progressive Growing of GANs for Improved Quality, Stability, and Variation

Reference 89

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Diffusion Model Quantization: A Review A style-based generator architecture for generative adversarial networks

Reference 90

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Diffusion Model Quantization: A Review Microsoft coco: Common objects in context

Reference 91

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Diffusion Model Quantization: A Review Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 92

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Diffusion Model Quantization: A Review Fs-coco: Towards understanding of freehand sketches of common objects in context

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Diffusion Model Quantization: A Review Magicanimate: Temporally consistent human image animation using diffusion model

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Diffusion Model Quantization: A Review Sparsec- trl: Adding sparse controls to text-to-video diffusion models

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Diffusion Model Quantization: A Review OPT: Open Pre-trained Transformer Language Models

Reference 96

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Diffusion Model Quantization: A Review Laion-5b: An open large-scale dataset for training next generation image-text models

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Diffusion Model Quantization: A Review PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis

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Diffusion Model Quantization: A Review Open-Sora: Democratizing Efficient Video Production for All

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Diffusion Model Quantization: A Review Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 100

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Diffusion Model Quantization: A Review Scene parsing through ade20k dataset

Reference 101

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