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Letian Gong

4 accepted papers

2026

G-VTM: A Multimodal Vision-Trajectory Model for Generalized Vehicle Trajectory Prediction

IJCAI 2026

Generalized vehicle trajectory prediction across diverse junctions, including urban intersections and roundabouts, remains a fundamental task in Cooperative Vehicle–Infrastructure Systems (CVIS). This study faces two key challenges: (1) Generalize across junctions with heterogeneous map semantics an

Cited by 0Scholar
2026

TrajAR: Long-Term Trajectory Prediction at Urban Intersections via Multi-scale Interaction Perception

IJCAI 2026

Accurate trajectory prediction of multiple road users at urban intersections--including motorized and nonmotorized vehicles and pedestrians--is critical for cooperative vehicle-infrastructure systems and intelligent transportation systems. This study focuses on multiple road users' trajectory predic

Cited by 0Scholar
2024

Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models

NeurIPS 2024poster

Location-based services (LBS) have accumulated extensive human mobility data on diverse behaviors through check-in sequences. These sequences offer valuable insights into users’ intentions and preferences. Yet, existing models analyzing check-in sequences fail to consider the semantics contained in…

Cited by 5SourcePDFScholar
2023

Contrastive Pre-training with Adversarial Perturbations for Check-In Sequence Representation Learning

AAAI 2023technical

A core step of mining human mobility data is to learn accurate representations for user-generated check-in sequences. The learned representations should be able to fully describe the spatial-temporal mobility patterns of users and the high-level semantics of traveling. However, existing check-in seq…