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Diffusion models have exhibited substantial success in text-to-image generation.
Denoising Diffusion Implicit Models
Song, J.; Meng, C.; and Ermon, S. 2020 · 2010
Earlier work this paper cites.
Score-based generative modeling through stochastic differential equations
Song, Y.; Sohl-Dickstein, J.; Kingma, D. P.; Kumar, A.; Ermon, S.; and Poole, B. 2020 · 2011
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.-Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Song, Y.; and Ermon, S. 2019 · 2019
Earlier work this paper cites.
Language models are few-shot learners
Brown, T. B.; Mann, B.; Ryder, N.; Subbiah, M.; Kaplan, J.; Dhariwal, P.; Neelakantan, A.; Shyam, P.; Sastry, G.; Askell, A.; Agarwal, S.; Herbert-Voss, A.; Krueger, G.; Henighan, T.; Child, R.; Ramesh, A.; Ziegler, D. M.; Wu, J.; Winter, C.; Hesse, C.; Chen, M.; Sigler, E.; Litwin, M.; Gray, S.; Chess, B.; Clark, J.; Berner, C.; McCandlish, S.; Radford, A.; Sutskever, I.; and Amodei, D. 2020 · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel, C.; Shazeer, N.; Roberts, A.; Lee, K.; Narang, S.; Matena, M.; Zhou, Y.; Li, W.; and Liu, P. J. 2020 · 2020
Earlier work this paper cites.
Improved techniques for training score-based generative models
Song, Y.; and Ermon, S. 2020 · 2020
Earlier work this paper cites.
Learning Transferable Visual Models from Natural Language Supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
Earlier work this paper cites.
LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs
Schuhmann, C.; Vencu, R.; Beaumont, R.; Kaczmarczyk, R.; Mullis, C.; Katta, A.; Coombes, T.; Jitsev, J.; and Komatsuzaki, A. 2021 · 2021
Earlier work this paper cites.
Palm: Scaling language modeling with pathways
Chowdhery, A.; Narang, S.; Devlin, J.; Bosma, M.; Mishra, G.; Roberts, A.; Barham, P.; Chung, H. W.; Sutton, C.; Gehrmann, S.; et al. 2022 · 2022
Earlier work this paper cites.
Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis
Feng, W.; He, X.; Fu, T.-J.; Jampani, V.; Akula, A. R.; Narayana, P.; Basu, S.; Wang, X. E.; and Wang, W. Y. 2022 · 2022
Earlier work this paper cites.
Compositional visual generation with composable diffusion models
Liu, N.; Li, S.; Du, Y.; Torralba, A.; and Tenenbaum, J. B. 2022 · 2022
Earlier work this paper cites.
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Nichol, A.; Dhariwal, P.; Ramesh, A.; Shyam, P.; Mishkin, P.; McGrew, B.; Sutskever, I.; and Chen, M. 2022 · 2022
Earlier work this paper cites.
Hierarchical text-conditional image generation with clip latents
Ramesh, A.; Dhariwal, P.; Nichol, A.; Chu, C.; and Chen, M. 2022 · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C.; Chan, W.; Saxena, S.; Li, L.; Whang, J.; Denton, E. L.; Ghasemipour, K.; Gontijo Lopes, R.; Karagol Ayan, B.; Salimans, T.; et al. 2022 · 2022
Cited alongside, same era.
What the daam: Interpreting stable diffusion using cross attention
Tang, R.; Liu, L.; Pandey, A.; Jiang, Z.; Yang, G.; Kumar, K.; Stenetorp, P.; Lin, J.; and Ture, F. 2022 · 2022
Cited alongside, same era.
Scaling autoregressive models for content-rich text-to-image generation
Sdxl: Improving latent diffusion models for high-resolution image synthesis
Podell, D.; English, Z.; Lacey, K.; Blattmann, A.; Dockhorn, T.; Müller, J.; Penna, J.; and Rombach, R. 2023 · 2023
Later among the works it cites.
Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Ruiz, N.; Li, Y.; Jampani, V.; Pritch, Y.; Rubinstein, M.; and Aberman, K. 2023 · 2023
Later among the works it cites.
Llama 2: Open foundation and fine-tuned chat models
Touvron, H.; Martin, L.; Stone, K.; Albert, P.; Almahairi, A.; Babaei, Y.; Bashlykov, N.; Batra, S.; Bhargava, P.; Bhosale, S.; et al. 2023 · 2023
Later among the works it cites.
Paragraph-to-image generation with information-enriched diffusion model
Wu, W.; Li, Z.; He, Y.; Shou, M. Z.; Shen, C.; Cheng, L.; Li, Y.; Gao, T.; Zhang, D.; and Wang, Z. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
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Yu, J.; Xu, Y.; Koh, J. Y.; Luong, T.; Baid, G.; Wang, Z.; Vasudevan, V.; Ku, A.; Yang, Y.; Ayan, B. K.; et al. 2022 · 2022
Cited alongside, same era.
Opt: Open pre-trained transformer language models
Zhang, S.; Roller, S.; Goyal, N.; Artetxe, M.; Chen, M.; Chen, S.; Dewan, C.; Diab, M.; Li, X.; Lin, X. V.; Mihaylov, T.; et al. 2022 · 2022
Cited alongside, same era.
Achiam, J.; Adler, S.; Agarwal, S.; Ahmad, L.; Akkaya, I.; Aleman, F. L.; Almeida, D.; Altenschmidt, J.; Altman, S.; Anadkat, S.; et al. 2023 · 2023
Cited alongside, same era.
Qwen-vl: A frontier large vision-language model with versatile abilities
Bai, J.; Bai, S.; Yang, S.; Wang, S.; Tan, S.; Wang, P.; Lin, J.; Zhou, C.; and Zhou, J. 2023 · 2023
Cited alongside, same era.
Improving image generation with better captions
Betker, J.; Goh, G.; Jing, L.; Brooks, T.; Wang, J.; Li, L.; Ouyang, L.; Zhuang, J.; Lee, J.; Guo, Y.; et al. 2023 · 2023
Cited alongside, same era.
A survey on evaluation of large language models
Chang, Y.; Wang, X.; Wang, J.; Wu, Y.; Yang, L.; Zhu, K.; Chen, H.; Yi, X.; Wang, C.; Wang, Y.; et al. 2023 · 2023
Cited alongside, same era.
Attend-and-excite: Attention-based semantic guidance for text-to-image diffusion models
Chefer, H.; Alaluf, Y.; Vinker, Y.; Wolf, L.; and Cohen-Or, D. 2023 · 2023
Cited alongside, same era.
T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation
Huang, K.; Sun, K.; Xie, E.; Li, Z.; and Liu, X. 2023 · 2023
Cited alongside, same era.
Zhong, S.; Huang, Z.; Wen, W.; Qin, J.; and Lin, L. 2023 · 2023
Later among the works it cites.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Zhu, D.; Chen, J.; Shen, X.; Li, X.; and Elhoseiny, M. 2023 · 2023
Later among the works it cites.
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
Hu, X.; Wang, R.; Fang, Y.; Fu, B.; Cheng, P.; and Yu, G. 2024 · 2024
Closest in time.
LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models
Lian, L.; Li, B.; Yala, A.; and Darrell, T. 2024 · 2024
Closest in time.
Frozen transformers in language models are effective visual encoder layers
Pang, Z.; Xie, Z.; Man, Y.; and Wang, Y.-X. 2024 · 2024
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Emu: Generative pretraining in multimodality
Sun, Q.; Yu, Q.; Cui, Y.; Zhang, F.; Zhang, X.; Wang, Y.; Gao, H.; Liu, J.; Huang, T.; and Wang, X. 2024 · 2024
Closest in time.
Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms
Yang, L.; Yu, Z.; Meng, C.; Xu, M.; Ermon, S.; and Cui, B. 2024 · 2024
Closest in time.
Llama-adapter: Efficient fine-tuning of language models with zero-init attention
Zhang, R.; Han, J.; Zhou, A.; Hu, X.; Yan, S.; Lu, P.; Li, H.; Gao, P.; and Qiao, Y. 2024 · 2024
Closest in time.
Bridging Different Language Models and Generative Vision Models for Text-to-Image Generation
Zhao, S.; Hao, S.; Zi, B.; Xu, H.; and Wong, K.-Y. K. 2024 · 2024
Closest in time.