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CBF-LLM: Safe Control for LLM Alignment

Published 28 Aug 2024 in eess.SY, cs.AI, cs.CL, and cs.SY | (2408.15625v2)

Abstract: This paper proposes a control-based framework for aligning LLMs by leveraging a control barrier function (CBF) to ensure user-desirable text generation. The presented framework applies the safety filter, designed based on the CBF, to the output generation of the baseline LLM, i.e., the sequence of the token, with the aim of intervening in the generated text. The overall text-generation system is implemented with Llama 3 and a RoBERTa model, and the source code is available at https://github.com/Mya-Mya/CBF-LLM. The experiment demonstrates its control ability and effectiveness in reducing the number of interventions needed for user-specified alignment tasks.

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