5 citations · 7 across the 7 of their papers we have counts for
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cs.GT2026★ 2 cited
Recruiting Heterogeneous Crowdsource Vehicles for Updating a High-definition Map
Wentao Ye, Yuan Luo, Bo Liu +1
The high-definition map is a cornerstone of autonomous driving. Unlike constructing a costly fleet of mapping vehicles, the crowdsourcing paradigm is a cost-effective way to keep a…
cs.GT2026★ 5 cited
Efficient and Cost-effective Vehicle Recruitment for HD Map Crowdsourcing
Wentao Ye, Yuan Luo, Bo Liu +1
The high-definition (HD) map is a cornerstone of autonomous driving. The crowdsourcing paradigm is a cost-effective way to keep an HD map up-to-date. Current HD map crowdsourcing m…
cs.GT2026
Mechanism Design for Federated Learning with Non-Monotonic Network Effects
Xiang Li, Bing Luo, Jianwei Huang +1
Mechanism design is pivotal to federated learning (FL) for maximizing social welfare by coordinating self-interested clients. Existing mechanisms, however, often overlook the netwo…