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Our world is marked by unprecedented technological, global, and socio-political transformations, posing a significant challenge to text-to-image generative models.
A simple neural network generating an interactive memory
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Correlation matrix memories
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Are there basic emotions?
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Modifying memories in transformer models
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Microsoft COCO: Common objects in context
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Man is to computer programmer as woman is to homemaker? debiasing word embeddings
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Overcoming catastrophic forgetting in neural networks
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Improving language understanding by generative pre-training
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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Rewriting a deep generative model
David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, and Antonio Torralba. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2020 · 2020
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Known unknowns: Learning novel concepts using reasoning-by-elimination
Harsh Agrawal, Eli A. Meirom, Yuval Atzmon, Shie Mannor, and Gal Chechik. 2021 · 2021
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David Bau, Alex Andonian, Audrey Cui, YeonHwan Park, Ali Jahanian, Aude Oliva, and Antonio Torralba. 2021 · 2021
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Editing factual knowledge in language models
Nicola De Cao, Wilker Aziz, and Ivan Titov. 2021 · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol. 2021 · 2021
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A mathematical framework for transformer circuits
Nelson Elhage, Neel Nanda, Catherine Olsson, Tom Henighan, Nicholas Joseph, Ben Mann, Amanda Askell, Yuntao Bai, Anna Chen, Tom Conerly, et al. 2021 · 2021
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Transformer feed-forward layers are key-value memories
Mor Geva, Roei Schuster, Jonathan Berant, and Omer Levy. 2021 · 2021
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CLIPScore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi. 2021 · 2021
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Creativegan: Editing generative adversarial networks for creative design synthesis
Amin Heyrani Nobari, Muhammad Fathy Rashad, and Faez Ahmed. 2021 · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021 · 2021
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Editing a classifier by rewriting its prediction rules
Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, and Aleksander Madry. 2021 · 2021
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Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried. 2022 · 2022
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Dall-eval: Probing the reasoning skills and social biases of text-to-image generative transformers
Jaemin Cho, Abhay Zala, and Mohit Bansal. 2022 · 2022
LAION-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade W Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, Patrick Schramowski, Srivatsa R Kundurthy, Katherine Crowson, Ludwig Schmidt, Robert Kaczmarczyk, and Jenia Jitsev. 2022 · 2022
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The biased artist: Exploiting cultural biases via homoglyphs in text-guided image generation models
Lukas Struppek, Dominik Hintersdorf, and Kristian Kersting. 2022 · 2022
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Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, and Thomas Wolf. 2022 · 2022
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Rewriting geometric rules of a gan
Sheng-Yu Wang, David Bau, and Jun-Yan Zhu. 2022 · 2022
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Unifying diffusion models’ latent space, with applications to cyclediffusion and guidance
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"this is my unicorn, fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Eli A. Meirom, Gal Chechik, and Yuval Atzmon. 2022 · 2022
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Knowledge neurons in pretrained transformers
Damai Dai, Li Dong, Yaru Hao, Zhifang Sui, Baobao Chang, and Furu Wei. 2022 · 2022
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Multiresolution textual inversion
Giannis Daras and Alexandros G. Dimakis. 2022 · 2022
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Torchmetrics - measuring reproducibility in pytorch
Nicki Skafte Detlefsen, Jiri Borovec, Justus Schock, Ananya Harsh Jha, Teddy Koker, Luca Di Liello, Daniel Stancl, Changsheng Quan, Maxim Grechkin, and William Falcon. 2022 · 2022
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Prompt-to-prompt image editing with cross attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or. 2022 · 2022
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans. 2022 · 2022
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Mind the gap: Understanding the modality gap in multi-modal contrastive representation learning
Victor Weixin Liang, Yuhui Zhang, Yongchan Kwon, Serena Yeung, and James Y Zou. 2022 · 2022
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Chen Henry Wu and Fernando De la Torre. 2022 · 2022
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Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, and Aylin Caliskan. 2023 · 2023
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Diffedit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk, and Matthieu Cord. 2023 · 2023
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A friendly face: Do text-to-image systems rely on stereotypes when the input is under-specified?
Kathleen C Fraser, Svetlana Kiritchenko, and Isar Nejadgholi. 2023 · 2023
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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. 2023 · 2023
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Imagic: Text-based real image editing with diffusion models
Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani. 2023 · 2023
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Mass-editing memory in a transformer
Kevin Meng, Arnab Sen Sharma, Alex J. Andonian, Yonatan Belinkov, and David Bau. 2023 · 2023
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Null-text inversion for editing real images using guided diffusion models
Ron Mokady, Amir Hertz, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or. 2023 · 2023
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Editing implicit assumptions in text-to-image diffusion models
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov. 2023 · 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 · 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 · 2023
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EDICT: exact diffusion inversion via coupled transformations
Bram Wallace, Akash Gokul, and Nikhil Naik. 2023 · 2023
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SINE: single image editing with text-to-image diffusion models
Zhixing Zhang, Ligong Han, Arnab Ghosh, Dimitris N. Metaxas, and Jian Ren. 2023 · 2023
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Diffusion lens: Interpreting text encoders in text-to-image pipelines
Michael Toker, Hadas Orgad, Mor Ventura, Dana Arad, and Yonatan Belinkov. 2024 · 2024
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