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In the era of AIGC, the demand for low-budget or even on-device applications of diffusion models emerged.
Distilling the knowledge in a neural network. In NeurIPS Workshop
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2014 · 2014
Earlier work this paper cites.
Fitnets: Hints for thin deep nets. In ICLR
Adriana Romero, Nicolas Ballas, Samira Ebrahimi Kahou, Antoine Chassang, Carlo Gatta, and Yoshua Bengio. 2015 · 2015
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium. In NeurIPS
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter. 2017 · 2017
Earlier work this paper cites.
Shallowing deep networks: Layer-wise pruning based on feature representations
Shi Chen and Qi Zhao. 2018 · 2018
Earlier work this paper cites.
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 2019
Earlier work this paper cites.
To filter prune, or to layer prune, that is the question. In ACCV
Sara Elkerdawy, Mostafa Elhoushi, Abhineet Singh, Hong Zhang, and Nilanjan Ray. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models. In NeurIPS
Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020 · 2020
Earlier work this paper cites.
Denoising Diffusion Implicit Models. In ICLR
Jiaming Song, Chenlin Meng, and Stefano Ermon. 2020 · 2020
Earlier work this paper cites.
Diffusion models beat gans on image synthesis. In NeurIPS
Prafulla Dhariwal and Alexander Nichol. 2021 · 2021
Earlier work this paper cites.
CLIPScore: A Reference-free Evaluation Metric for Image Captioning. In EMNLP
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi. 2021 · 2021
Earlier work this paper cites.
Classifier-Free Diffusion Guidance. In NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications
Jonathan Ho and Tim Salimans. 2021 · 2021
Earlier work this paper cites.
Learning transferable visual models from natural language supervision. In ICML
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
Zero-shot text-to-image generation. In ICML
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. 2021 · 2021
Earlier work this paper cites.
Score-Based Generative Modeling through Stochastic Differential Equations. In ICLR
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole. 2021 · 2021
Earlier work this paper cites.
A study on the evaluation of generative models
Eyal Betzalel, Coby Penso, Aviv Navon, and Ethan Fetaya. 2022 · 2022
Cited alongside, same era.
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow. In ICLR
Xingchao Liu, Chengyue Gong, et al · 2022
Cited alongside, same era.
Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2022b · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding. In NeurIPS
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Cited alongside, same era.
Progressive Distillation for Fast Sampling of Diffusion Models. In ICLR
Tim Salimans and Jonathan Ho. 2022 · 2022
Stable-diffusion-xl-base-1.0
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach. 2023 · 2023
Later among the works it cites.
Adversarial diffusion distillation
Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach. 2023 · 2023
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Realistic Vision
SG_161222. 2023 · 2023
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Post-training quantization on diffusion models. In CVPR
Yuzhang Shang, Zhihang Yuan, Bin Xie, Bingzhe Wu, and Yan Yan. 2023 · 2023
Later among the works it cites.
ProtoVision XL
socalguitarist. 2023 · 2023
Later among the works it cites.
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Cited alongside, same era.
RDO-Q: Extremely Fine-Grained Channel-Wise Quantization via Rate-Distortion Optimization. In ECCV
Zhe Wang, Jie Lin, Xue Geng, Mohamed M Sabry Aly, and Vijay Chandrasekhar. 2022 · 2022
Cited alongside, same era.
If by deepfloyd lab at stabilityai
Daria Bakshandaeva Christoph Schuhmann Ksenia Ivanova Alex Shonenkov, Misha Konstantinov and Nadiia Klokova. 2023 · 2023
Cited alongside, same era.
Sdxl-vae-fp16-fix
Ollin Boer Bohan. 2023 · 2023
Cited alongside, same era.
Speed is all you need: On-device acceleration of large diffusion models via gpu-aware optimizations. In CVPR
Yu-Hui Chen, Raman Sarokin, Juhyun Lee, Jiuqiang Tang, Chuo-Ling Chang, Andrei Kulik, and Matthias Grundmann. 2023 · 2023
Cited alongside, same era.
On architectural compression of text-to-image diffusion models
Bo-Kyeong Kim, Hyoung-Kyu Song, Thibault Castells, and Shinkook Choi. 2023 · 2023
Cited alongside, same era.
Youngwan Lee, Kwanyong Park, Yoorhim Cho, Yong-Ju Lee, and Sung Ju Hwang. 2023 · 2023
Cited alongside, same era.
Faster diffusion: Rethinking the role of unet encoder in diffusion models
Senmao Li, Taihang Hu, Fahad Shahbaz Khan, Linxuan Li, Shiqi Yang, Yaxing Wang, Ming-Ming Cheng, and Jian Yang. 2023a · 2023
Cited alongside, same era.
Xiaoshi Wu, Yiming Hao, Keqiang Sun, Yixiong Chen, Feng Zhu, Rui Zhao, and Hongsheng Li. 2023a · 2023
Later among the works it cites.
Ufogen: You forward once large scale text-to-image generation via diffusion gans
Yanwu Xu, Yang Zhao, Zhisheng Xiao, and Tingbo Hou. 2023d · 2023
Later among the works it cites.
ZavyChromaXL
Zavy. 2023 · 2023
Later among the works it cites.
MobileDiffusion: Subsecond Text-to-Image Generation on Mobile Devices
Yang Zhao, Yanwu Xu, Zhisheng Xiao, and Tingbo Hou. 2023 · 2023
Later among the works it cites.
Structural pruning for diffusion models. In NeurIPS
Gongfan Fang, Xinyin Ma, and Xinchao Wang. 2024 · 2024
Closest in time.
Progressive Knowledge Distillation Of Stable Diffusion XL Using Layer Level Loss
Yatharth Gupta, Vishnu V Jaddipal, Harish Prabhala, Sayak Paul, and Patrick Von Platen. 2024 · 2024
Closest in time.
Shortened LLaMA: A Simple Depth Pruning for Large Language Models
Bo-Kyeong Kim, Geonmin Kim, Tae-Ho Kim, Thibault Castells, Shinkook Choi, Junho Shin, and Hyoung-Kyu Song. 2024 · 2024
Closest in time.
SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis. In ICLR
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach. 2024 · 2024
Closest in time.