Fetching the paper…
Reading the bibliography…
Latent diffusion models (LDMs) exhibit an impressive ability to produce realistic images, yet the inner workings of these models remain mysterious.
Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Understanding intermediate layers using linear classifier probes
Guillaume Alain and Yoshua Bengio · 2016
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
What you can cram into a single vector: Probing sentence embeddings for linguistic properties
Alexis Conneau, German Kruszewski, Guillaume Lample, Loïc Barrault, and Marco Baroni · 2018
Earlier work this paper cites.
Kelly W Zhang and Samuel R Bowman · 2018
Earlier work this paper cites.
Do neural language representations learn physical commonsense?
Maxwell Forbes, Ari Holtzman, and Yejin Choi · 2019
Earlier work this paper cites.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, Alexander H Miller, and Sebastian Riedel · 2019
Earlier work this paper cites.
Bert rediscovers the classical nlp pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick · 2019
Earlier work this paper cites.
Climbing towards nlu: On meaning, form, and understanding in the age of data
Emily M Bender and Alexander Koller · 2020
Earlier work this paper cites.
Experience grounds language
Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, and Joseph Turian · 2020
Earlier work this paper cites.
Analyzing analytical methods: The case of phonology in neural models of spoken language
Grzegorz Chrupała, Bertrand Higy, and Afra Alishahi · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Self-supervised monocular trained depth estimation using self-attention and discrete disparity volume
Adrian Johnston and Gustavo Carneiro · 2020
Cited alongside, same era.
Label-efficient semantic segmentation with diffusion models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, and Artem Babenko · 2021
Cited alongside, same era.
Probing classifiers: Promises, shortcomings, and alternatives
Yonatan Belinkov · 2021
Cited alongside, same era.
Amnesic probing: Behavioral explanation with amnesic counterfactuals
Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
Later among the works it cites.
Dag: Depth-aware guidance with denoising diffusion probabilistic models
Gyeongnyeon Kim, Wooseok Jang, Gyuseong Lee, Susung Hong, Junyoung Seo, and Seungryong Kim · 2022
Later among the works it cites.
Tracer: Extreme attention guided salient object tracing network (student abstract)
Min Seok Lee, WooSeok Shin, and Sung Won Han · 2022
Later among the works it cites.
Emergent world representations: Exploring a sequence model trained on a synthetic task
Kenneth Li, Aspen K Hopkins, David Bau, Fernanda Viégas, Hanspeter Pfister, and Martin Wattenberg · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yanai Elazar, Shauli Ravfogel, Alon Jacovi, and Yoav Goldberg · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Vision transformers for dense prediction
René Ranftl, Alexey Bochkovskiy, and Vladlen Koltun · 2021
Cited alongside, same era.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
Cited alongside, same era.
What if this modified that? syntactic interventions via counterfactual embeddings
Mycal Tucker, Peng Qian, and Roger Levy · 2021
Cited alongside, same era.
Stability ai raises seed round at $1 billion value
Mureji Fatunde and Crystal Tse · 2022
Cited alongside, same era.
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
Later among the works it cites.
Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2022
Later among the works it cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Later among the works it cites.
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
Later among the works it cites.
Score jacobian chaining: Lifting pretrained 2d diffusion models for 3d generation
Haochen Wang, Xiaodan Du, Jiahao Li, Raymond A Yeh, and Greg Shakhnarovich · 2022
Later among the works it cites.
Geofill: Reference-based image inpainting with better geometric understanding
Yunhan Zhao, Connelly Barnes, Yuqian Zhou, Eli Shechtman, Sohrab Amirghodsi, and Charless Fowlkes · 2023
Closest in time.