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As large language models (LLMs) become increasingly prevalent across many real-world applications, understanding and enhancing their robustness to adversarial attacks is of paramount importance.
The theory of statistical decision
L. J. Savage · 1951
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
Generating automatic curricula via self-supervised active domain randomization
Sharath Chandra Raparthy, Bhairav Mehta, Florian Golemo, and Liam Paull · 2002
Earlier work this paper cites.
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Chin-Yew Lin and Franz Josef Och · 2004
Earlier work this paper cites.
Abandoning objectives: Evolution through the search for novelty alone
Joel Lehman and Kenneth O Stanley · 2011
Earlier work this paper cites.
Illuminating search spaces by mapping elites, 2015
Jean-Baptiste Mouret and Jeff Clune · 2015
Earlier work this paper cites.
Quality diversity: A new frontier for evolutionary computation
Justin K Pugh, Lisa B Soros, and Kenneth O Stanley · 2016
Earlier work this paper cites.
Quality and diversity optimization: A unifying modular framework
Antoine Cully and Yiannis Demiris · 2017
Earlier work this paper cites.
Automated curriculum learning for neural networks
Alex Graves, Marc G Bellemare, Jacob Menick, Remi Munos, and Koray Kavukcuoglu · 2017
Earlier work this paper cites.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer · 2017
Earlier work this paper cites.
Texygen: A benchmarking platform for text generation models
Yaoming Zhu, Sidi Lu, Lei Zheng, Jiaxian Guo, Weinan Zhang, Jun Wang, and Yong Yu · 2018
Earlier work this paper cites.
Emergent complexity and zero-shot transfer via unsupervised environment design
Michael Dennis, Natasha Jaques, Eugene Vinitsky, Alexandre Bayen, Stuart Russell, Andrew Critch, and Sergey Levine · 2020
Earlier work this paper cites.
Active domain randomization
Bhairav Mehta, Manfred Diaz, Florian Golemo, Christopher J. Pal, and Liam Paull · 2020
Earlier work this paper cites.
Bertscore: Evaluating text generation with bert, 2020
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi · 2020
Earlier work this paper cites.
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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman · 2021
Earlier work this paper cites.
On the importance of environments in human-robot coordination
Matthew C Fontaine, Ya-Chuan Hsu, Yulun Zhang, Bryon Tjanaka, and Stefanos Nikolaidis · 2021
Earlier work this paper cites.
Measuring massive multitask language understanding, 2021
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2021
Earlier work this paper cites.
Replay-guided adversarial environment design
Minqi Jiang, Michael Dennis, Jack Parker-Holder, Jakob Foerster, Edward Grefenstette, and Tim Rocktäschel · 2021
Earlier work this paper cites.
Dynabench: Rethinking benchmarking in nlp
Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, et al · 2021
Earlier work this paper cites.
Deep surrogate assisted generation of environments
Varun Bhatt, Bryon Tjanaka, Matthew Fontaine, and Stefanos Nikolaidis · 2022
Earlier work this paper cites.
Evaluating human–robot interaction algorithms in shared autonomy via quality diversity scenario generation
Matthew C Fontaine and Stefanos Nikolaidis · 2022
Earlier work this paper cites.
Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned, 2022
Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, Andy Jones, Sam Bowman, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El-Showk, Stanislav Fort, Zac Hatfield-Dodds, Tom Henighan, Danny Hernandez, Tristan Hume, Josh Jacobson, Scott Johnston, Shauna Kravec, Catherine Olsson, Sam Ringer, Eli Tran-Johnson, Dario Amodei, Tom Brown, Nicholas Joseph, Sam McCandlish, Chris Olah, Jared Kaplan, and Jack Clark · 2022
Earlier work this paper cites.
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Dan Hendrycks, Nicholas Carlini, John Schulman, and Jacob Steinhardt · 2022
Earlier work this paper cites.
Evolution through large models, 2022
Joel Lehman, Jonathan Gordon, Shawn Jain, Kamal Ndousse, Cathy Yeh, and Kenneth O. Stanley · 2022
Earlier work this paper cites.
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Sören Mindermann, Jan M Brauner, Muhammed T Razzak, Mrinank Sharma, Andreas Kirsch, Winnie Xu, Benedikt Höltgen, Aidan N Gomez, Adrien Morisot, Sebastian Farquhar, et al · 2022
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Smoothllm: Defending large language models against jailbreaking attacks
Alexander Robey, Eric Wong, Hamed Hassani, and George J Pappas · 2023
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Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve · 2023
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Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov, and David Krueger · 2022
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Large language models in medicine
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