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Recent advancements in image generation models have enabled personalized image creation with both user-defined subjects (content) and styles.
Hypernetworks
David Ha, Andrew M. Dai, and Quoc V. Le · 2017
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
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Ziyi Dong, Pengxu Wei, and Liang Lin · 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 Haim Bermano, Gal Chechik, and Daniel Cohen-or · 2022
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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Mitchell Wortsman, Gabriel Ilharco, Samir Ya Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, et al · 2022
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Domain-agnostic tuning-encoder for fast personalization of text-to-image models
Moab Arar, Rinon Gal, Yuval Atzmon, Gal Chechik, Daniel Cohen-Or, Ariel Shamir, and Amit H. Bermano · 2023
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Encoder-based domain tuning for fast personalization of text-to-image models
Rinon Gal, Moab Arar, Yuval Atzmon, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2023
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Mix-of-show: Decentralized low-rank adaptation for multi-concept customization of diffusion models
Yuchao Gu, Xintao Wang, Jay Zhangjie Wu, Yujun Shi, Yunpeng Chen, Zihan Fan, WUYOU XIAO, Rui Zhao, Shuning Chang, Weijia Wu, Yixiao Ge, Ying Shan, and Mike Zheng Shou · 2023
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Svdiff: Compact parameter space for diffusion fine-tuning
Ligong Han, Yinxiao Li, Han Zhang, Peyman Milanfar, Dimitris Metaxas, and Feng Yang · 2023
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Vico: Plug-and-play visual condition for personalized text-to-image generation
Shaozhe Hao, Kai Han, Shihao Zhao, and Kwan-Yee K Wong · 2023
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Editing models with task arithmetic
Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi · 2023
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Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Styledrop: Text-to-image synthesis of any style
Kihyuk Sohn, Lu Jiang, Jarred Barber, Kimin Lee, Nataniel Ruiz, Dilip Krishnan, Huiwen Chang, Yuanzhen Li, Irfan Essa, Michael Rubinstein, Yuan Hao, Glenn Entis, Irina Blok, and Daniel Castro Chin · 2023
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Key-locked rank one editing for text-to-image personalization
Yoad Tewel, Rinon Gal, Gal Chechik, and Yuval Atzmon · 2023
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p+: Extended textual conditioning in text-to-image generation
Andrey Voynov, Qinghao Chu, Daniel Cohen-Or, and Kfir Aberman · 2023
Cited alongside, same era.
Elite: Encoding visual concepts into textual embeddings for customized text-to-image generation
Yuxiang Wei, Yabo Zhang, Zhilong Ji, Jinfeng Bai, Lei Zhang, and Wangmeng Zuo · 2023
Cited alongside, same era.
Controllable textual inversion for personalized text-to-image generation
Jianan Yang, Haobo Wang, Yanming Zhang, Ruixuan Xiao, Sai Wu, Gang Chen, and Junbo Zhao · 2023
Cited alongside, same era.
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
Cited alongside, same era.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2023
Blip-diffusion: Pre-trained subject representation for controllable text-to-image generation and editing
Dongxu Li, Junnan Li, and Steven CH Hoi · 2024
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Subject-diffusion: Open domain personalized text-to-image generation without test-time fine-tuning
Jian Ma, Junhao Liang, Chen Chen, and Haonan Lu · 2024
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Kosmos-g: Generating images in context with multimodal large language models
Xichen Pan, Li Dong, Shaohan Huang, Zhiliang Peng, Wenhu Chen, and Furu Wei · 2024
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λ \lambda -ECLIPSE: Multi-concept personalized text-to-image diffusion models by leveraging CLIP latent space
Maitreya Patel, Sangmin Jung, Chitta Baral, and Yezhou Yang · 2024
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SDXL: Improving latent diffusion models for high-resolution image synthesis
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2024
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Cited alongside, same era.
Non-linear fusion in federated learning: A hypernetwork approach to federated domain generalization
Marc Bartholet, Taehyeon Kim, Ami Beuret, Se-Young Yun, and Joachim M Buhmann · 2024
Cited alongside, same era.
A study of parameter efficient fine-tuning by learning to efficiently fine-tune
Taha Ceritli, Savas Ozkan, Jeongwon Min, Eunchung Noh, Cho Min, and Mete Ozay · 2024
Cited alongside, same era.
A brief review of hypernetworks in deep learning
Vinod Kumar Chauhan, Jiandong Zhou, Ping Lu, Soheila Molaei, and David A Clifton · 2024
Cited alongside, same era.
Civitai: The Home of Open-Source Generative AI
Civitai · 2024
Cited alongside, same era.
Low-rank adaptation for fast text-to-image diffusion finetuning
Clonesofimo · 2024
Cited alongside, same era.
Implicit style-content separation using b-lora
Yarden Frenkel, Yael Vinker, Ariel Shamir, and Daniel Cohen-Or · 2024
Cited alongside, same era.
Arcee’s mergekit: A toolkit for merging large language models
Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, Luke Meyers, Vladimir Karpukhin, Brian Benedict, Mark McQuade, and Jacob Solawetz · 2024
Cited alongside, same era.
Bootpig: Bootstrapping zero-shot personalized image generation capabilities in pretrained diffusion models
Senthil Purushwalkam, Akash Gokul, Shafiq Joty, and Nikhil Naik · 2024
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HyperDreamBooth: HyperNetworks for Fast Personalization of Text-to-Image Models
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Wei Wei, Tingbo Hou, Yael Pritch, Neal Wadhwa, Michael Rubinstein, and Kfir Aberman · 2024
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Ziplora: Any subject in any style by effectively merging loras
Viraj Shah, Nataniel Ruiz, Forrester Cole, Erika Lu, Svetlana Lazebnik, Yuanzhen Li, and Varun Jampani · 2024
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Difflora: Generating personalized low-rank adaptation weights with diffusion
Yujia Wu, Yiming Shi, Jiwei Wei, Chengwei Sun, Yuyang Zhou, Yang Yang, and Heng Tao Shen · 2024
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Ties-merging: Resolving interference when merging models
Prateek Yadav, Derek Tam, Leshem Choshen, Colin A Raffel, and Mohit Bansal · 2024
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Language models are super mario: Absorbing abilities from homologous models as a free lunch
Le Yu, Bowen Yu, Haiyang Yu, Fei Huang, and Yongbin Li · 2024
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Dreamcache: Finetuning-free lightweight personalized image generation via feature caching
Emanuele Aiello, Umberto Michieli, Diego Valsesia, Mete Ozay, and Enrico Magli · 2025
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Dreambench++: A human-aligned benchmark for personalized image generation
Yuang Peng, Yuxin Cui, Haomiao Tang, Zekun Qi, Runpei Dong, Jing Bai, Chunrui Han, Zheng Ge, Xiangyu Zhang, and Shu-Tao Xia · 2025
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Rb-modulation: Training-free stylization using reference-based modulation
L Rout, Y Chen, N Ruiz, A Kumar, C Caramanis, S Shakkottai, and W Chu · 2025
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Llava-critic: Learning to evaluate multimodal models
Tianyi Xiong, Xiyao Wang, Dong Guo, Qinghao Ye, Haoqi Fan, Quanquan Gu, Heng Huang, and Chunyuan Li · 2025
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VL-ICL bench: The devil in the details of multimodal in-context learning
Yongshuo Zong, Ondrej Bohdal, and Timothy Hospedales · 2025
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