4 papers
Learning to Incentivize: LLM-Empowered Contract for AIGC Offloading in Teleoperation
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +4
With the rapid growth in demand for AI-generated content (AIGC), edge AIGC service providers (ASPs) have become indispensable. However, designing incentive mechanisms that motivate…
A Reliable Vertical Federated Learning Framework for Traffic State Estimation with Data Selection and Incentive Mechanisms
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +4
Vertical Federated Learning (VFL)-based Traffic State Estimation (TSE) offers a promising approach for integrating vertically distributed traffic data from municipal authorities (M…
Distributionally Robust Contract Theory for Edge AIGC Services in Teleoperation
Zijun Zhan, Yaxian Dong, Daniel Mawunyo Doe +5
Advanced AI-Generated Content (AIGC) technologies have injected new impetus into teleoperation, further enhancing its security and efficiency. Edge AIGC networks have been introduc…
Vision Language Model-Empowered Contract Theory for AIGC Task Allocation in Teleoperation
Zijun Zhan, Yaxian Dong, Yuqing Hu +3
Integrating low-light image enhancement techniques, in which diffusion-based AI-generated content (AIGC) models are promising, is necessary to enhance nighttime teleoperation. Rema…