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The practical use of text-to-image generation has evolved from simple, monolithic models to complex workflows that combine multiple specialized components.
A statistical interpretation of term specificity and its application in retrieval
Karen Sparck Jones · 1972
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen · 2021
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Stable diffusion web-ui
AUTOMATIC1111 · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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High-resolution image synthesis with latent diffusion models
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Laion-5b: An open large-scale dataset for training next generation image-text models
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Improving image generation with better captions
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Emu: Enhancing image generation models using photogenic needles in a haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, et al · 2023
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Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2023
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Improving sample quality of diffusion models using self-attention guidance
Susung Hong, Gyuseong Lee, Wooseok Jang, and Seungryong Kim · 2023
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Dspy: Compiling declarative language model calls into self-improving pipelines
Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T Joshi, Hanna Moazam, et al · 2023
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Pick-a-pic: An open dataset of user preferences for text-to-image generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2023
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Aligning text-to-image models using human feedback
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, and Shixiang Shane Gu · 2023
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Lcm-lora: A universal stable-diffusion acceleration module, 2023
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Can generalist foundation models outcompete special-purpose tuning? case study in medicine
Harsha Nori, Yin Tat Lee, Sheng Zhang, Dean Carignan, Richard Edgar, Nicolo Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, Weishung Liu, et al · 2023
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Aligning text-to-image diffusion models with reward backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, and Katerina Fragkiadaki · 2023
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Low-rank adaptation for fast text-to-image diffusion fine-tuning
Simo Ryu · 2023
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A picture is worth a thousand words: Principled recaptioning improves image generation
Eyal Segalis, Dani Valevski, Danny Lumen, Yossi Matias, and Yaniv Leviathan · 2023
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Vipergpt: Visual inference via python execution for reasoning
Dídac Surís, Sachit Menon, and Carl Vondrick · 2023
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
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Freeenhance: Tuning-free image enhancement via content-consistent noising-and-denoising process
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Not all noises are created equally: Diffusion noise selection and optimization
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Direct preference optimization: Your language model is secretly a reward model
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Ip-adapter: Text compatible image prompt adapter for text-to-image diffusion models
Hu Ye, Jun Zhang, Sibo Liu, Xiao Han, and Wei Yang · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Alphacode 2 technical report
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Directly fine-tuning diffusion models on differentiable rewards
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Toolformer: Language models can teach themselves to use tools
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