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Deployed multimodal systems can fail in ways that evaluators did not anticipate.
The protection of information in computer systems
Jerome H Saltzer and Michael D Schroeder · 1975
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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
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A large annotated corpus for learning natural language inference
Samuel R Bowman, Gabor Angeli, Christopher Potts, and Christopher D Manning · 2015
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Man is to computer programmer as woman is to homemaker? Debiasing word embeddings
Tolga Bolukbasi, Kai-Wei Chang, James Y Zou, Venkatesh Saligrama, and Adam T Kalai · 2016
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Learning adversary-resistant deep neural networks
Qinglong Wang, Wenbo Guo, Kaixuan Zhang, Alexander G Ororbia II, Xinyu Xing, Xue Liu, and C Lee Giles · 2016
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Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J Bryson, and Arvind Narayanan · 2017
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Defending against adversarial samples without security through obscurity
Wenbo Guo, Qinglong Wang, Kaixuan Zhang, Alexander G Ororbia, Sui Huang, Xue Liu, C Lee Giles, Lin Lin, and Xinyu Xing · 2018
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Towards accountable ai: Hybrid human-machine analyses for characterizing system failure
Besmira Nushi, Ece Kamar, and Eric Horvitz · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Hila Gonen and Yoav Goldberg · 2019
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Bias correction of learned generative models using likelihood-free importance weighting
Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric J Horvitz, and Stefano Ermon · 2019
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On measuring social biases in sentence encoders
Chandler May, Alex Wang, Shikha Bordia, Samuel R Bowman, and Rachel Rudinger · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng · 2019
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Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, et al · 2019
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Mitigating gender bias in natural language processing: Literature review
Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, and William Yang Wang · 2019
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Do nlp models know numbers? probing numeracy in embeddings
Eric Wallace, Yizhong Wang, Sujian Li, Sameer Singh, and Matt Gardner · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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What bert is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Allyson Ettinger · 2020
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith · 2020
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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
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Adversarial semantic collisions
Congzheng Song, Alexander Rush, and Vitaly Shmatikov · 2020
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Persistent anti-muslim bias in large language models
Abubakar Abid, Maheen Farooqi, and James Zou · 2021
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On the dangers of stochastic parrots: Can language models be too big?
Emily Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchel · 2021
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Stereotyping norwegian salmon: An inventory of pitfalls in fairness benchmark datasets
Su Lin Blodgett, Gilsinia Lopez, Alexandra Olteanu, Robert Sim, and Hanna Wallach · 2021
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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, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, and Percy Liang · 2021
High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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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
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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
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Explaining patterns in data with language models via interpretable autoprompting
Chandan Singh, John X Morris, Jyoti Aneja, Alexander M Rush, and Jianfeng Gao · 2022
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Winoground: Probing vision and language models for visio-linguistic compositionality
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom B Brown, Dawn Song, Ulfar Erlingsson, et al · 2021
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Algorithmic monoculture and social welfare
Jon M. Kleinberg and Manish Raghavan · 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
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Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
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Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, and Iason Gabriel · 2021
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Picking on the same person: Does algorithmic monoculture lead to outcome homogenization?
Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, and Percy Liang · 2022
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Testing relational understanding in text-guided image generation
Colin Conwell and Tomer Ullman · 2022
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Domino: Discovering systematic errors with cross-modal embeddings
Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, and Christopher Ré · 2022
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Tristan Thrush, Ryan Jiang, Max Bartolo, Amanpreet Singh, Adina Williams, Douwe Kiela, and Candace Ross · 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
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Discovering bugs in vision models using off-the-shelf image generation and captioning
Olivia Wiles, Isabela Albuquerque, and Sven Gowal · 2022
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Describing differences between text distributions with natural language
Ruiqi Zhong, Charlie Snell, Dan Klein, and Jacob Steinhardt · 2022
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“Introducing Claude ‘’
Anthropic · 2023
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Language models can explain neurons in language models
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Introducing ChatGPT and Whisper APIs
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Extracting training data from diffusion models
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Automatically auditing large language models via discrete optimization
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Shap-e: Generating conditional 3d implicit functions
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Videofusion: Decomposed diffusion models for high-quality video generation
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Identification of systematic errors of image classifiers on rare subgroups
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If by deepfloyd lab at stabilityai
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Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery
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When and why vision-language models behave like bags-of-words, and what to do about it?
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Diagnosing and rectifying vision models using language
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Goal driven discovery of distributional differences via language descriptions
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