Abstract: Machine learning plays a crucial role in autonomous vehicles, particularly in driver assistance technologies that enhance driving efficiency or eliminate the need for human intervention. One ...

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...

Abstract: Adversarial Machine Learning (AML) is a fascinating and fast-growing research direction and area of practical interest. Deployed Machine Learning (ML) models are known to be vulnerable to ...

ABSTRACT: To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating ...

Corresponding repo for "Busting the Ballot: Voting Meets Adversarial Machine Learning". We show the security risk associated with using machine learning classifiers in United States election ...

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...

The National Institute of Standards and Technology has issued a document that identifies threats associated with adversarial machine learning. The Adversarial Machine Learning: A Taxonomy and ...