Concept Ablation Fine-Tuning (CAFT) uses interpretability tools to steer LLM generalization away from unintended concepts without altering training data. Fine-tuning large language models (LLMs) can lead to unintended out-of-distribution generalization. Standard approaches to this problem rely…
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Concept Ablation Fine-Tuning (CAFT) uses interpretability tools to steer LLM generalization away from unintended concepts without altering training…
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