Papers by Kai Williams
Immunization against harmful fine-tuning attacks (2024.findings-emnlp)
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| Challenge: | Large Language Models are often trained with safety guards to prevent harmful text generation. |
| Approach: | They propose a formal framework based on the training budget of an attacker to validate defenses against harmful fine-tuning attacks. |
| Outcome: | The proposed framework validates whether a model has been fine-tuned against harmful fine-uning attacks on harmful datasets. |