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The objective of personalization and stylization in text-to-image is to instruct a pre-trained diffusion model to analyze new concepts introduced by users and incorporate them into expected styles.
Multi-concept customization of text-to-image diffusion
Kumari, N.; Zhang, B.; Zhang, R.; Shechtman, E.; and Zhu, J.-Y. 2023 · 1941
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Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning
Liu, H.; Tam, D.; Muqeeth, M.; Mohta, J.; Huang, T.; Bansal, M.; and Raffel, C. A. 2022 · 1965
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Parameter-efficient transfer learning for NLP
Houlsby, N.; Giurgiu, A.; Jastrzebski, S.; Morrone, B.; De Laroussilhe, Q.; Gesmundo, A.; Attariyan, M.; and Gelly, S. 2019 · 2019
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Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
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DeepDanbooru:AI based multi-label girl image classification system, implemented by using TensorFlow
Kim, K. 2020 · 2020
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Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning
Aghajanyan, A.; Gupta, S.; and Zettlemoyer, L. 2021 · 2021
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Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation
Gheini, M.; Ren, X.; and May, J. 2021 · 2021
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LoRA: Low-Rank Adaptation of Large Language Models
Hu, E. J.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; Chen, W.; et al. 2021 · 2021
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Compacter: Efficient low-rank hypercomplex adapter layers
Karimi Mahabadi, R.; Henderson, J.; and Ruder, S. 2021 · 2021
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Manga Faces Dataset:Manga Faces Dataset classified with facial expressions classes
Köklü, M. 2021 · 2021
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Improved denoising diffusion probabilistic models
Nichol, A. Q.; and Dhariwal, P. 2021 · 2021
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Training neural networks with fixed sparse masks
Sung, Y.-L.; Nair, V.; and Raffel, C. A. 2021 · 2021
Cited alongside, same era.
Pufferfish: Communication-efficient models at no extra cost
Wang, H.; Agarwal, S.; and Papailiopoulos, D. 2021 · 2021
Cited alongside, same era.
ediffi: Text-to-image diffusion models with an ensemble of expert denoisers
Balaji, Y.; Nah, S.; Huang, X.; Vahdat, A.; Song, J.; Kreis, K.; Aittala, M.; Aila, T.; Laine, S.; Catanzaro, B.; et al. 2022 · 2022
Cited alongside, same era.
Adaptformer: Adapting vision transformers for scalable visual recognition
Chen, S.; Ge, C.; Tong, Z.; Wang, J.; Song, Y.; Wang, J.; and Luo, P. 2022 · 2022
Cited alongside, same era.
Krona: Parameter efficient tuning with kronecker adapter
Edalati, A.; Tahaei, M.; Kobyzev, I.; Nia, V. P.; Clark, J. J.; and Rezagholizadeh, M. 2022 · 2022
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Svdiff: Compact parameter space for diffusion fine-tuning
Han, L.; Li, Y.; Zhang, H.; Milanfar, P.; Metaxas, D.; and Yang, F. 2023 · 2023
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Fact: Factor-tuning for lightweight adaptation on vision transformer
Jie, S.; and Deng, Z.-H. 2023 · 2023
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Large-scale text-to-image generation models for visual artists’ creative works
Ko, H.-K.; Park, G.; Jeon, H.; Jo, J.; Kim, J.; and Seo, J. 2023 · 2023
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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
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StyleDrop: Text-to-Image Generation in Any Style
Sohn, K.; Ruiz, N.; Lee, K.; Chin, D. C.; Blok, I.; Chang, H.; Barber, J.; Jiang, L.; Entis, G.; Li, Y.; et al. 2023 · 2023
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Scaling & shifting your features: A new baseline for efficient model tuning
Lian, D.; Zhou, D.; Feng, J.; and Wang, X. 2022 · 2022
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Low-rank adaptation for fast text-to-image diffusion fine-tuning
Ryu, S. 2022 · 2022
Cited alongside, same era.
Lst: Ladder side-tuning for parameter and memory efficient transfer learning
Sung, Y.-L.; Cho, J.; and Bansal, M. 2022 · 2022
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Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Zhang, Q.; Chen, M.; Bukharin, A.; He, P.; Cheng, Y.; Chen, W.; and Zhao, T. 2022 · 2022
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One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning
Chavan, A.; Liu, Z.; Gupta, D.; Xing, E.; and Shen, Z. 2023 · 2023
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Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models
Gu, Y.; Wang, X.; Wu, J. Z.; Shi, Y.; Chen, Y.; Fan, Z.; Xiao, W.; Zhao, R.; Chang, S.; Wu, W.; et al. 2023 · 2023
Cited alongside, same era.
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Gal, R.; Alaluf, Y.; Atzmon, Y.; Patashnik, O.; Bermano, A. H.; Chechik, G.; and Cohen-or, D. 2022a
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DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation
Valipour, M.; Rezagholizadeh, M.; Kobyzev, I.; and Ghodsi, A. 2023 · 2023
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P + P+ : Extended Textual Conditioning in Text-to-Image Generation
Voynov, A.; Chu, Q.; Cohen-Or, D.; and Aberman, K. 2023 · 2023
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Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
Wang, K.; Yang, F.; Yang, S.; Butt, M. A.; and van de Weijer, J. 2023 · 2023
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Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
Yeh, S.-Y.; Hsieh, Y.-G.; Gao, Z.; Yang, B. B. W.; Oh, G.; and Gong, Y. 2023 · 2023
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The Impact of Generative Artificial Intelligence
Zhang, K.; Kwon, O.; and Xiong, H. 2023 · 2023
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