arXiv Machine Learning August 12, 2026 By Alexander Schi{\o}tz, Bertram Hage, Christian Rand, Felix Thomsen, Peder Heiselberg

CRHT: A Continuous Regression Hybrid Transformer for Vessel Trajectory Prediction with Online Cluster Sampling

Read the original on arXiv Machine Learning →

arXiv:2608. 10256v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is critical for maritime safety and anomaly detection, yet existing models often struggle with geographic bias and navigational realism.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning

Aug 4

EnvShip: A Unified Framework for Context-Aware and Cross-Region Vessel Trajectory Forecasting

arXiv:2606. 15240v2 Announce Type: replace Abstract: Accurate vessel trajectory forecasting is essential for maritime situational awareness, navigation safety, traffic management, and autonomous navigation.

By Kun Ma, Qilong Han, Chengjing Song, Jingzheng Yao, Hao Wang, Changmao Wu

agents safety

arXiv Machine Learning

Jul 31

Context-Informed Ship Trajectory Prediction via Conditional Attention

arXiv:2607. 27418v1 Announce Type: new Abstract: Long-term ship trajectory prediction is a fundamental capability for maritime safety and autonomous navigation.

By Yuan Guan, Chandler Squires, Timothy Hu, Pradeep Ravikumar

llms agents multimodal safety

arXiv Machine Learning

2d ago

Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling

arXiv:2608. 14349v1 Announce Type: new Abstract: We present a training-free method for multi-modal trajectory prediction that achieves comparable accuracy to a 57M-parameter transformer while requiring no GPU and zero learned parameters.

By Michael Fore, Akshay Jain, Justin Downes, Rohan Pradhan, Duncan Botti

llms multimodal benchmarks

arXiv Machine Learning

Jun 16

EnvShip-Bench: An Environment-Enhanced Benchmark for Short-Term Vessel Trajectory Prediction

arXiv:2606. 15240v1 Announce Type: new Abstract: Vessel trajectory prediction is important for intelligent shipping, maritime surveillance, and navigation safety.

By Kun Ma, Qilong Han, Chengjing Song, Jingzheng Yao, Hao Wang, Changmao Wu

benchmarks safety data-engineering

arXiv AI

Jul 22

SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction

arXiv:2601. 18537v4 Announce Type: replace-cross Abstract: Accurate long-horizon vessel trajectory prediction remains challenging due to compounded uncertainty from complex navigation behaviors and environmental factors.

By Linyong Gan, Zimo Li, Wenxin Xu, Xingjian Li, Jianhua Z. Huang, Enmei Tu, Shuhang Chen

benchmarks

arXiv AI

Jun 6

AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks

arXiv:2606. 06311v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is essential for safe and efficient maritime operations, enabling collision avoidance and supporting route optimization.

By Wonmo Koo, Sanha Chang, Heeyoung Kim

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EnvShip: A Unified Framework for Context-Aware and Cross-Region Vessel Trajectory Forecasting

Context-Informed Ship Trajectory Prediction via Conditional Attention

Non-Parametric Spatiotemporal Trajectory Prediction via State-Conditioned Transition Sampling

EnvShip-Bench: An Environment-Enhanced Benchmark for Short-Term Vessel Trajectory Prediction

SKETCH: Semantic Key-Point Conditioning for Long-Horizon Vessel Trajectory Prediction

AIS-Based Vessel Trajectory Prediction Using Memory-Augmented Neural Networks