AI RESEARCH
TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning
arXiv CS.LG
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ArXi:2605.20134v1 Announce Type: new Learning generalizable trajectory representations from raw GPS traces remains difficult because the data is continuous, noisy, and irregularly sampled. Spatial tokenization is also challenging: fine grids yield sparse cells with weak embeddings, while coarse grids merge heterogeneous movement patterns into the same token. We present TrajTok, a trajectory encoder with a simple pre