This AI Paper Introduces RuLES: A New Machine Learning Framework for Assessing Rule-Adherence in Large Language Models Against Adversarial Attacks

In response to the increasing deployment of LLMs with real-world responsibilities, a programmatic framework called Rule-following Language Evaluation Scenarios (RULES) is proposed by a group of researchers from UC Berkeley, Center for AI Safety, Stanford, King Abdulaziz City for Science and Technology. RULES comprises 15 text scenarios with specific rules for model behavior, allowing for […]

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