2 papers
cs.CL2025
MobQA: A Benchmark Dataset for Semantic Understanding of Human Mobility Data through Question Answering
Hikaru Asano, Hiroki Ouchi, Akira Kasuga +1
This paper presents MobQA, a benchmark dataset designed to evaluate the semantic understanding capabilities of large language models (LLMs) for human mobility data through natural…
cs.CL2024
Text2Traj2Text: Learning-by-Synthesis Framework for Contextual Captioning of Human Movement Trajectories
Hikaru Asano, Ryo Yonetani, Taiki Sekii +1
This paper presents Text2Traj2Text, a novel learning-by-synthesis framework for captioning possible contexts behind shopper's trajectory data in retail stores. Our work will impact…