Humzah Merchant
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126
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NLP×1
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2026
Divergence Decoding: Inference-Time Unlearning via Auxiliary Models
Divergence Decoding (DD) is a novel, effective, and inexpensive method that uses auxiliary models to steer LLM logits during inference, enabling the removal of memorized sensitive data without significant utility loss.
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