Fetching the paper…
Reading the bibliography…
While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reasoning such as logic and comparison.
Problems of monetary management: the UK experience
Charles AE Goodhart and CAE Goodhart · 1984
Earlier work this paper cites.
‘improving ratings’: audit in the british university system
Marilyn Strathern · 1997
Earlier work this paper cites.
The emperor has no clothes: Limits to risk modelling
Jón Danıelsson · 2002
Earlier work this paper cites.
Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
Earlier work this paper cites.
Goodhart’s law
Charles Goodhart · 2015
Earlier work this paper cites.
Watch out for cheats in citation game
Mario Biagioli · 2016
Earlier work this paper cites.
Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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
Earlier work this paper cites.
On the value of out-of-distribution testing: An example of goodhart’s law
Damien Teney, Ehsan Abbasnejad, Kushal Kafle, Robik Shrestha, Christopher Kanan, and Anton Van Den Hengel · 2020
Earlier work this paper cites.
Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
Earlier work this paper cites.
The h-index is no longer an effective correlate of scientific reputation
Vladlen Koltun and David Hafner · 2021
Earlier work this paper cites.
Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
Earlier work this paper cites.
Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum · 2022
Earlier work this paper cites.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Earlier work this paper cites.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
Earlier work this paper cites.
Make-a-video: Text-to-video generation without text-video data
Uriel Singer, Adam Polyak, Thomas Hayes, Xi Yin, Jie An, Songyang Zhang, Qiyuan Hu, Harry Yang, Oron Ashual, Oran Gafni, et al · 2022
Cited alongside, same era.
Unifying language learning paradigms
Yi Tay, Mostafa Dehghani, Vinh Q Tran, Xavier Garcia, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Neil Houlsby, and Donald Metzler · 2022
Cited alongside, same era.
Winoground: Probing vision and language models for visio-linguistic compositionality
Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross · 2022
Cited alongside, same era.
Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
Cited alongside, same era.
Llmscore: Unveiling the power of large language models in text-to-image synthesis evaluation
Yujie Lu, Xianjun Yang, Xiujun Li, Xin Eric Wang, and William Yang Wang · 2023
Later among the works it cites.
OpenAI · 2023
Later among the works it cites.
Toward verifiable and reproducible human evaluation for text-to-image generation
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, and Shin’ichi Satoh · 2023
Later among the works it cites.
Aligning text-to-image diffusion models with reward backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, and Katerina Fragkiadaki · 2023
Later among the works it cites.
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
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
When and why vision-language models behave like bags-of-words, and what to do about it?
Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, and James Zou · 2022
Cited alongside, same era.
Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
Cited alongside, same era.
Training diffusion models with reinforcement learning
Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, and Sergey Levine · 2023
Cited alongside, same era.
Muse: Text-to-image generation via masked generative transformers
Huiwen Chang, Han Zhang, Jarred Barber, AJ Maschinot, Jose Lezama, Lu Jiang, Ming-Hsuan Yang, Kevin Murphy, William T Freeman, Michael Rubinstein, et al · 2023
Cited alongside, same era.
Ties matter: Meta-evaluating modern metrics with pairwise accuracy and tie calibration
Daniel Deutsch, George Foster, and Markus Freitag · 2023
Cited alongside, same era.
Goodhart’s law applies to nlp’s explanation benchmarks
Jennifer Hsia, Danish Pruthi, Aarti Singh, and Zachary C Lipton · 2023
Cited alongside, same era.
Tifa: Accurate and interpretable text-to-image faithfulness evaluation with question answering
Yushi Hu, Benlin Liu, Jungo Kasai, Yizhong Wang, Mari Ostendorf, Ranjay Krishna, and Noah A Smith · 2023
Cited alongside, same era.
T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation
Kaiyi Huang, Kaiyue Sun, Enze Xie, Zhenguo Li, and Xihui Liu · 2023
Cited alongside, same era.
Later among the works it cites.
Jaskirat Singh and Liang Zheng · 2023
Later among the works it cites.
Diffusion model alignment using direct preference optimization
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, and Nikhil Naik · 2023
Later among the works it cites.
Imagereward: Learning and evaluating human preferences for text-to-image generation
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2023
Later among the works it cites.
What you see is what you read? improving text-image alignment evaluation
Michal Yarom, Yonatan Bitton, Soravit Changpinyo, Roee Aharoni, Jonathan Herzig, Oran Lang, Eran Ofek, and Idan Szpektor · 2023
Later among the works it cites.
Deepfloyd IF
Deepfloyd IF · 2024
Closest in time.
Versat2i: Improving text-to-image models with versatile reward
Jianshu Guo, Wenhao Chai, Jie Deng, Hsiang-Wei Huang, Tian Ye, Yichen Xu, Jiawei Zhang, Jenq-Neng Hwang, and Gaoang Wang · 2024
Closest in time.
GenAI-bench: A holistic benchmark for compositional text-to-visual generation
Baiqi Li, Zhiqiu Lin, Deepak Pathak, Jiayao Emily Li, Xide Xia, Graham Neubig, Pengchuan Zhang, and Deva Ramanan · 2024
Closest in time.
Language models as black-box optimizers for vision-language models
Shihong Liu, Zhiqiu Lin, Samuel Yu, Ryan Lee, Tiffany Ling, Deepak Pathak, and Deva Ramanan · 2024
Closest in time.
Improving text-to-image consistency via automatic prompt optimization
Oscar Mañas, Pietro Astolfi, Melissa Hall, Candace Ross, Jack Urbanek, Adina Williams, Aishwarya Agrawal, Adriana Romero-Soriano, and Michal Drozdzal · 2024
Closest in time.
Midjourney
Midjourney · 2024
Closest in time.
Docci: Descriptions of connected and contrasting images
Yasumasa Onoe, Sunayana Rane, Zachary Berger, Yonatan Bitton, Jaemin Cho, Roopal Garg, Alexander Ku, Zarana Parekh, Jordi Pont-Tuset, Garrett Tanzer, et al · 2024
Closest in time.
The neglected tails of vision-language models
Shubham Parashar, Zhiqiu Lin, Tian Liu, Xiangjue Dong, Yanan Li, Deva Ramanan, James Caverlee, and Shu Kong · 2024
Closest in time.
When do we not need larger vision models?
Baifeng Shi, Ziyang Wu, Maolin Mao, Xin Wang, and Trevor Darrell · 2024
Closest in time.