Proposes FL+DP for offloading time-series transformer training in 6G vehicles, claiming 75% accuracy at ε=0.8, but lacks the described algorithms and has incorrect composition accounting.
A survey on the applications of frontier ai, foundation models, and large language models to intelligent trans- portation systems,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CR 1years
2025 1verdicts
REJECT 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
Privacy-Preserving Offloading for Large Language Models in 6G Vehicular Networks
Proposes FL+DP for offloading time-series transformer training in 6G vehicles, claiming 75% accuracy at ε=0.8, but lacks the described algorithms and has incorrect composition accounting.