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Nanyang Technological University, Singapore, Digital Trust Centre Singapore
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HiCore's innovative use of multi-hypergraphs enables it to significantly reduce the bias towards popular items in conversational recommendations, achieving unprecedented fairness in user engagement.
The first comprehensive framework for understanding the security risks and defenses of mobile on-device AI systems reveals critical gaps that could jeopardize user privacy and data integrity.
Uncovering critical security and privacy vulnerabilities in foundation-model-powered robots could redefine how we approach their deployment in real-world applications.
MIXGUARD achieves robust privacy protection in split learning without sacrificing model utility, outperforming existing defenses against advanced data reconstruction attacks.
LLM agents are shockingly vulnerable to stealthy economic DoS attacks that inflate costs by up to 658x, even while returning correct answers.
