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---
title: README
emoji: 🌍
colorFrom: red
colorTo: yellow
sdk: static
pinned: false
---
# Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs
Abhay Sheshadri,* [[email protected]]([email protected]);
Aidan Ewart,* [[email protected]]([email protected]);
Phillip Guo,* [[email protected]]([email protected]);
Aengus Lynch,* [[email protected]]([email protected]);
Cindy Wu,* [[email protected]]([email protected]);
Vivek Hebbar*;
Henry Sleight;
Asa Cooper Stickland;
Ethan Perez;
Dylan Hadfield-Menell;
Stephen Casper, [[email protected]]([email protected])
See our [GitHub:](https://github.com/aengusl/latent-adversarial-training).
Read the paper on arXiv: [Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs](https://arxiv.org/abs/2407.15549).
Chat with our robust refusal model ([https://huggingface.co./LLM-LAT/robust-llama3-8b-instruct](https://huggingface.co./LLM-LAT/robust-llama3-8b-instruct)) at [https://www.abhayesian.com/lat-chat](https://www.abhayesian.com/lat-chat).
```
@article{sheshadri2024targeted,
title={Targeted Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs},
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},
journal={arXiv preprint arXiv:2407.15549},
year={2024}
}
```
See also preliminary work: [Defending Against Unforeseen Failure Modes with Latent Adversarial Training](https://arxiv.org/abs/2403.05030). |