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Collections including paper arxiv:2310.12004

Exploiting Diffusion Prior for Real-World Image Super-Resolution

Paper • 2305.07015 • Published May 11, 2023 • 4
Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder Approach

Paper • 2310.12004 • Published Oct 18, 2023 • 2
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild

Paper • 2401.13627 • Published Jan 24 • 72
StreamDiffusion: A Pipeline-level Solution for Real-time Interactive Generation

Paper • 2312.12491 • Published Dec 19, 2023 • 69

MOE papers to read

Copied from MoE using https://huggingface.co/spaces/librarian-bots/collection_cloner.

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

Image Super-resolution Via Latent Diffusion: A Sampling-space Mixture Of Experts And Frequency-augmented Decoder Approach

Paper • 2310.12004 • Published Oct 18, 2023 • 2
Concept-free Causal Disentanglement with Variational Graph Auto-Encoder

Paper • 2311.10638 • Published Nov 17, 2023 • 2
Tokenization with Factorized Subword Encoding

Paper • 2306.07764 • Published Jun 13, 2023 • 1
Mixture-of-experts VAEs can disregard variation in surjective multimodal data

Paper • 2204.05229 • Published Apr 11, 2022 • 1

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 26
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

Sparse Autoencoders Find Highly Interpretable Features in Language Models

Paper • 2309.08600 • Published Sep 15, 2023 • 13
In-context Autoencoder for Context Compression in a Large Language Model

Paper • 2307.06945 • Published Jul 13, 2023 • 27
Self-slimmed Vision Transformer

Paper • 2111.12624 • Published Nov 24, 2021 • 1
MEMORY-VQ: Compression for Tractable Internet-Scale Memory

Paper • 2308.14903 • Published Aug 28, 2023 • 1

Woodpecker: Hallucination Correction for Multimodal Large Language Models

Paper • 2310.16045 • Published Oct 24, 2023 • 14
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models

Paper • 2310.14566 • Published Oct 23, 2023 • 25
SILC: Improving Vision Language Pretraining with Self-Distillation

Paper • 2310.13355 • Published Oct 20, 2023 • 6
Conditional Diffusion Distillation

Paper • 2310.01407 • Published Oct 2, 2023 • 20

FreeU: Free Lunch in Diffusion U-Net

Paper • 2309.11497 • Published Sep 20, 2023 • 64
Imagic: Text-Based Real Image Editing with Diffusion Models

Paper • 2210.09276 • Published Oct 17, 2022
On Architectural Compression of Text-to-Image Diffusion Models

Paper • 2305.15798 • Published May 25, 2023 • 4
Wuerstchen: Efficient Pretraining of Text-to-Image Models

Paper • 2306.00637 • Published Jun 1, 2023 • 12

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