arXiv Machine Learning#tech
M-CTX: Exact and Scalable Spatial Context Retrieval for Trajectory Analyticstranslating…
Factuality: 61/100UnknownarXiv Digital Media
arXiv:2606.15244v1 Announce Type: new
Abstract: Modern trajectory predictors increasingly condition on external spatial context, such as map geometry, signed distance fields (SDFs), and nearby moving agents. While this context improves prediction quality, constructing it for every training anchor has become a hidden systems bottleneck. In a representative maritime AIS pipeline, spatial context construction requires roughly 17 CPU-days for a 5.48M-anchor corpus, dominating the cost of the downst