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We present the Pathways Autoregressive Text-to-Image (Parti) model, which generates high-fidelity photorealistic images and supports content-rich synthesis involving complex compositions and world knowledge.
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Adafactor: Adaptive learning rates with sublinear memory cost
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Inferring semantic layout for hierarchical text-to-image synthesis
Seunghoon Hong, Dingdong Yang, Jongwook Choi, and Honglak Lee · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Chatpainter: Improving text to image generation using dialogue
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Megatron-lm: Training multi-billion parameter language models using model parallelism, 2019
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper, and Bryan Catanzaro · 2019
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Generating long sequences with sparse transformers
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Lingvo: a modular and scalable framework for sequence-to-sequence modeling
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Generating multiple objects at spatially distinct locations
Tobias Hinz, Stefan Heinrich, and Stefan Wermter · 2019
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Model cards for model reporting
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Tell, draw, and repeat: Generating and modifying images based on continual linguistic instruction
Alaaeldin El-Nouby, Shikhar Sharma, Hannes Schulz, Devon Hjelm, Layla El Asri, Samira Ebrahimi Kahou, Yoshua Bengio, and Graham W Taylor · 2019
Scaling vision transformers, 2021
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer · 2021
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Simvlm: Simple visual language model pretraining with weak supervision
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Text-to-image generation grounded by fine-grained user attention
Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang · 2021
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Cross-modal contrastive learning for text-to-image generation
Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang · 2021
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Benchmark for compositional text-to-image synthesis
Dong Huk Park, Samaneh Azadi, Xihui Liu, Trevor Darrell, and Anna Rohrbach · 2021
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Vector quantized diffusion model for text-to-image synthesis
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Does object recognition work for everyone?
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Transformer transducer: A streamable speech recognition model with transformer encoders and rnn-t loss
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Conformer: Convolution-augmented transformer for speech recognition
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Connecting vision and language with localized narratives
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Shuyang Gu, Dong Chen, Jianmin Bao, Fang Wen, Bo Zhang, Dongdong Chen, Lu Yuan, and Baining Guo · 2021
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Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Unifying vision-and-language tasks via text generation
Jaemin Cho, Jie Lei, Hao Tan, and Mohit Bansal · 2021
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mindall-e on conceptual captions
Chiheon Kim Doyup Lee Saehoon Kim, Sanghun Cho and Woonhyuk Baek · 2021
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How to marry a star: Probabilistic constraints for meaning in context
Katrin Erk and Aurélie Herbelot · 2021
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Dall·e mini, 7 2021
Boris Dayma, Suraj Patil, Pedro Cuenca, Khalid Saifullah, Tanishq Abraham, Phuc Le Khac, Luke Melas, and Ritobrata Ghosh · 2021
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Learning transferable visual models from natural language supervision
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Towards accountability for machine learning datasets: Practices from software engineering and infrastructure
Ben Hutchinson, Andrew Smart, Alex Hanna, Emily Denton, Christina Greer, Oddur Kjartansson, Parker Barnes, and Margaret Mitchell · 2021
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On the genealogy of machine learning datasets: A critical history of ImageNet
Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, and Hilary Nicole · 2021
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Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé III, and Kate Crawford · 2021
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Biases in generative art: A causal look from the lens of art history
Ramya Srinivasan and Kanji Uchino · 2021
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Paraphrase generation: A survey of the state of the art
Jianing Zhou and Suma Bhat · 2021
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Multimodal datasets: misogyny, pornography, and malignant stereotypes
Abeba Birhane, Vinay Uday Prabhu, and Emmanuel Kahembwe · 2021
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Make-a-scene: Scene-based text-to-image generation with human priors
Oran Gafni, Adam Polyak, Oron Ashual, Shelly Sheynin, Devi Parikh, and Yaniv Taigman · 2022
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