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Exploring Unsupervised Methods for Recovering the Refusal Direction in LLMs

This study explores unsupervised methods, including principal component analysis and Isomap, alongside difference-in-means to investigate the refusal direction in LLMs. Experiments are conducted on Llama 8b 3.1 Instruct and Qwen2.5-7B-Instruct models using Alpaca and Beavertails datasets.

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Tracking sinceOctober 22, 20267 source points
Momentum—More observations needed
PublishedOctober 22, 2026dinosaue
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This research could help in understanding the mechanisms behind refusal in language models, which is important for improving their reliability and safety.

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