Immunization against harmful fine-tuning attacks

Deep-lock: Secure authorization for deep neural networks

Original

Manaar Alam, Sayandeep Saha, Debdeep Mukhopadhyay, and Sandip Kundu. 2020 · 2008

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Realtoxicityprompts: Evaluating neural toxic degeneration in language models

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Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 2020 · 2009

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Measuring massive multitask language understanding

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Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2009

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A theory of learning from different domains

Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, and Jennifer Wortman Vaughan. 2010 · 2010

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Pointer sentinel mixture models

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Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016

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Dynamics and reachability of learning tasks

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The GEM benchmark: Natural language generation, its evaluation and metrics

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Lora: Low-rank adaptation of large language models

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Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021

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Non-Transferable Learning: A New Approach for Model Ownership Verification and Applicability Authorization

Lixu Wang, Shichao Xu, Ruiqi Xu, Xiao Wang, and Qi Zhu. 2021 · 2021

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"real attackers don’t compute gradients": Bridging the gap between adversarial ml research and practice

Original

Giovanni Apruzzese, Hyrum S. Anderson, Savino Dambra, David Freeman, Fabio Pierazzi, and Kevin A. Roundy. 2022 · 2022

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Spinning language models: Risks of propaganda-as-a-service and countermeasures

Eugene Bagdasaryan and Vitaly Shmatikov. 2022 · 2022

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Taxonomy of Risks posed by Language Models

Laura Weidinger, Jonathan Uesato, Maribeth Rauh, Conor Griffin, Po-Sen Huang, John Mellor, Amelia Glaese, Myra Cheng, Borja Balle, Atoosa Kasirzadeh, Courtney Biles, Sasha Brown, Zac Kenton, Will Hawkins, Tom Stepleton, Abeba Birhane, Lisa Anne Hendricks, Laura Rimell, William Isaac, Julia Haas, Sean Legassick, Geoffrey Irving, and Iason Gabriel. 2022 · 2022

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Language model unalignment: Parametric red-teaming to expose hidden harms and biases

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Rishabh Bhardwaj and Soujanya Poria. 2023 · 2023

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Stealthy and persistent unalignment on large language models via backdoor injections

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Yuanpu Cao, Bochuan Cao, and Jinghui Chen. 2023 · 2023

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ROBBIE: Robust bias evaluation of large generative language models

David Esiobu, Xiaoqing Tan, Saghar Hosseini, Megan Ung, Yuchen Zhang, Jude Fernandes, Jane Dwivedi-Yu, Eleonora Presani, Adina Williams, and Eric Smith. 2023 · 2023

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Badllama: cheaply removing safety fine-tuning from llama 2-chat 13b

Original

Pranav Gade, Simon Lermen, Charlie Rogers-Smith, and Jeffrey Ladish. 2023 · 2023

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Not what you’ve signed up for: Compromising real-world llm-integrated applications with indirect prompt injection

Original

Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, Christoph Endres, Thorsten Holz, and Mario Fritz. 2023 · 2023

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Large language models can be used to effectively scale spear phishing campaigns

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Julian Hazell. 2023 · 2023

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Self-destructing models: Increasing the costs of harmful dual uses of foundation models

Peter Henderson, Eric Mitchell, Christopher Manning, Dan Jurafsky, and Chelsea Finn. 2023b · 2023

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Editing models with task arithmetic

Original

Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, Suchin Gururangan, Ludwig Schmidt, Hannaneh Hajishirzi, and Ali Farhadi. 2023 · 2023

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Llama guard: Llm-based input-output safeguard for human-ai conversations

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Hakan Inan, Kartikeya Upasani, Jianfeng Chi, Rashi Rungta, Krithika Iyer, Yuning Mao, Michael Tontchev, Qing Hu, Brian Fuller, Davide Testuggine, et al. 2023 · 2023

Cited alongside, same era.

Mechanistically analyzing the effects of fine-tuning on procedurally defined tasks

Original

Samyak Jain, Robert Kirk, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka, Edward Grefenstette, Tim Rocktäschel, and David Scott Krueger. 2023 · 2023

Cited alongside, same era.

Learning and forgetting unsafe examples in large language models

Original

Jiachen Zhao, Zhun Deng, David Madras, James Zou, and Mengye Ren. 2023 · 2023

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Making harmful behaviors unlearnable for large language models

Original

Xin Zhou, Yi Lu, Ruotian Ma, Tao Gui, Qi Zhang, and Xuanjing Huang. 2023 · 2023

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Universal and transferable adversarial attacks on aligned language models

Original

Andy Zou, Zifan Wang, Nicholas Carlini, Milad Nasr, J. Zico Kolter, and Matt Fredrikson. 2023 · 2023

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Foundational challenges in assuring alignment and safety of large language models

Original

Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob Foerster, Florian Tramer, He He, Atoosa Kasirzadeh, Yejin Choi, and David Krueger. 2024 · 2024