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M3-Former: Multimodal Transformer with Mixture-of-Experts for Long-Term Vessel Trajectory Prediction
Not provided in the abstract
multimodaltrajectory predictionMixture-of-Expertssemantic modeling
2609.10559
Builder Relevance
4h ago70%
Abstract
This paper proposes M3-Former, a multimodal trajectory prediction framework that enhances long-term vessel trajectory prediction by incorporating large language models and semantic priors.
Reality Card
Core Claim
M3-Former reduces Average Displacement Error (ADE) and Final Displacement Error (FDE) by 4.4% and 5.1%, respectively, compared to the strongest baseline in 4-hour prediction tasks.
Method / Result
Achieved a 4.4% reduction in Average Displacement Error (ADE) in long-term trajectory prediction.
Limitations
The paper does not specify the authors or provide detailed implementation guidelines, which may hinder reproducibility.
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