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# Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs
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Abhay Sheshadri,* [asheshadri31@gatech.edu](asheshadri31@gatech.edu);
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Aidan Ewart,* [aidanprattewart@gmail.com](aidanprattewart@gmail.com);
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Phillip Guo,* [phguo@umd.edu](phguo@umd.edu);
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Aengus Lynch,* [aenguslynch@gmail.com](aenguslynch@gmail.com);
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Cindy Wu,* [wu.cindyx@gmail.com](wu.cindyx@gmail.com);
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Vivek Hebbar*;
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Henry Sleight;
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Asa Cooper Stickland;
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Ethan Perez;
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Dylan Hadfield-Menell;
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Stephen Casper, [scasper@mit.edu](scasper@mit.edu)
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See our [GitHub:](https://github.com/aengusl/latent-adversarial-training).
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Read the paper on arXiv: [Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs](https://arxiv.org/abs/2407.15549).
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```
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@article{sheshadri2024targeted,
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title={Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs},
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author={Sheshadri, Abhay and Ewart, Aidan and Guo, Phillip and Lynch, Aengus and Wu, Cindy and Hebbar, Vivek and Sleight, Henry and Stickland, Asa Cooper and Perez, Ethan and Hadfield-Menell, Dylan and Casper, Stephen},
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journal={arXiv preprint arXiv:2407.15549},
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year={2024}
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}
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```
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See also preliminary work: [Defending Against Unforeseen Failure Modes with Latent Adversarial Training](https://arxiv.org/abs/2403.05030).
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