Fetching the paper…
Reading the bibliography…
Text-to-image diffusion models (T2I) use a latent representation of a text prompt to guide the image generation process.
On a test of whether one of two random variables is stochastically larger than the other
Henry B Mann and Donald R Whitney. 1947 · 1947
Earlier work this paper cites.
International encyclopedia of the social & behavioral sciences , volume 11
Neil J Smelser, Paul B Baltes, et al. 2001 · 2001
Earlier work this paper cites.
Perceptual simulation in conceptual combination: Evidence from property generation
Ling ling Wu and Lawrence W. Barsalou. 2009 · 2009
Earlier work this paper cites.
Conceptual combination 1
James Hampton. 2013 · 2013
Earlier work this paper cites.
Visualizing and understanding convolutional networks
Matthew D. Zeiler and Rob Fergus. 2014 · 2014
Earlier work this paper cites.
Learning deep features for scene recognition using places database
Bolei Zhou, Agata Lapedriza, Jianxiong Xiao, Antonio Torralba, and Aude Oliva. 2014 · 2014
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, and Piotr Dollár. 2015 · 2015
Earlier work this paper cites.
Probing for semantic evidence of composition by means of simple classification tasks
Allyson Ettinger, Ahmed Elgohary, and Philip Resnik. 2016 · 2016
Earlier work this paper cites.
Network dissection: Quantifying interpretability of deep visual representations
David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, and Antonio Torralba. 2017 · 2017
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 · 2017
Earlier work this paper cites.
Visualisation and ’diagnostic classifiers’ reveal how recurrent and recursive neural networks process hierarchical structure
Dieuwke Hupkes, Sara Veldhoen, and Willem Zuidema. 2018 · 2018
Earlier work this paper cites.
Analysis methods in neural language processing: A survey
Yonatan Belinkov and James Glass. 2019 · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Analyzing redundancy in pretrained transformer models
Fahim Dalvi, Hassan Sajjad, Nadir Durrani, and Yonatan Belinkov. 2020 · 2020
Earlier work this paper cites.
Interpreting GPT: The logit lens. lesswrong, 2020
nostalgebraist. 2020 · 2020
Earlier work this paper cites.
Stanza: A python natural language processing toolkit for many human languages
Peng Qi, Yuhao Zhang, Yuhui Zhang, Jason Bolton, and Christopher D Manning. 2020 · 2020
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2020 · 2020
Earlier work this paper cites.
A primer in BERTology: What we know about how BERT works
Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2020 · 2020
Cited alongside, same era.
Investigating gender bias in language models using causal mediation analysis
Jesse Vig, Sebastian Gehrmann, Yonatan Belinkov, Sharon Qian, Daniel Nevo, Yaron Singer, and Stuart Shieber. 2020 · 2020
Cited alongside, same era.
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
Cited alongside, same era.
Amnesic probing: Behavioral explanation with amnesic counterfactuals
Yanai Elazar, Shauli Ravfogel, Alon Jacovi, and Yoav Goldberg. 2021 · 2021
Cited alongside, same era.
Multimodal neurons in artificial neural networks
Gabriel Goh, Nick Cammarata, Chelsea Voss, Shan Carter, Michael Petrov, Ludwig Schubert, Alec Radford, and Chris Olah. 2021 · 2021
Cited alongside, same era.
Openclip
When are lemons purple? the concept association bias of CLIP
Yutaro Yamada, Yingtian Tang, and Ilker Yildirim. 2022 · 2022
Later among the works it cites.
ReFACT: Updating text-to-image models by editing the text encoder
Dana Arad, Hadas Orgad, and Yonatan Belinkov. 2023 · 2023
Later among the works it cites.
Eliciting latent predictions from transformers with the tuned lens
Nora Belrose, Zach Furman, Logan Smith, Danny Halawi, Igor Ostrovsky, Lev McKinney, Stella Biderman, and Jacob Steinhardt. 2023 · 2023
Later among the works it cites.
Jump to conclusions: Short-cutting transformers with linear transformations
Alexander Yom Din, Taelin Karidi, Leshem Choshen, and Mor Geva. 2023 · 2023
Later among the works it cites.
Interpreting CLIP’s image representation via text-based decomposition
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt. 2021 · 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 · 2021
Cited alongside, same era.
Probing classifiers: Promises, shortcomings, and advances
Yonatan Belinkov. 2022 · 2022
Cited alongside, same era.
Transformer feed-forward layers build predictions by promoting concepts in the vocabulary space
Mor Geva, Avi Caciularu, Kevin Wang, and Yoav Goldberg. 2022 · 2022
Cited alongside, same era.
Post-hoc interpretability for neural NLP: A survey
Andreas Madsen, Siva Reddy, and Sarath Chandar. 2022 · 2022
Cited alongside, same era.
Locating and editing factual associations in GPT
Kevin Meng, David Bau, Alex Andonian, and Yonatan Belinkov. 2022 · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with CLIP latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022 · 2022
Cited alongside, same era.
Yossi Gandelsman, Alexei A Efros, and Jacob Steinhardt. 2023 · 2023
Later among the works it cites.
Prompt-to-prompt image editing with cross-attention control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or. 2023 · 2023
Later among the works it cites.
Visit: Visualizing and interpreting the semantic information flow of transformers
Shahar Katz and Yonatan Belinkov. 2023 · 2023
Later among the works it cites.
Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023 · 2023
Later among the works it cites.
OpenAI. 2023 · 2023
Later among the works it cites.
Editing implicit assumptions in text-to-image diffusion models
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov. 2023 · 2023
Later among the works it cites.
Future lens: Anticipating subsequent tokens from a single hidden state
Koyena Pal, Jiuding Sun, Andrew Yuan, Byron Wallace, and David Bau. 2023 · 2023
Later among the works it cites.
Deepfloyd if
StabilityAI. 2023 · 2023
Later among the works it cites.
What the DAAM: Interpreting stable diffusion using cross attention
Raphael Tang, Linqing Liu, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Pontus Stenetorp, Jimmy Lin, and Ferhan Ture. 2023 · 2023
Later among the works it cites.
Towards best practices of activation patching in language models: Metrics and methods
Fred Zhang and Neel Nanda. 2023 · 2023
Later among the works it cites.
A primer on the inner workings of transformer-based language models
Javier Ferrando, Gabriele Sarti, Arianna Bisazza, and Marta R Costa-jussà. 2024 · 2024
Closest in time.
Generating images of rare concepts using pre-trained diffusion models
Dvir Samuel, Rami Ben-Ari, Simon Raviv, Nir Darshan, and Gal Chechik. 2024 · 2024
Closest in time.