Papers by Clara Haya Suslik

1 papers
Precise In-Parameter Concept Erasure in Large Language Models (2025.emnlp-main)

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Challenge: Existing methods for erasing concepts from model parameters are either too coarse, shallow or ineffective.
Approach: They propose a framework for precisely erasing entire concepts from model parameters by directly editing directions that encode them in parameter space.
Outcome: The proposed framework reduces errors on the target concept to as low as 7.7% while improving specificity and robustness.

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