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SKDU at De-Factify 4.0: Natural Language Features for AI-Generated Text-Detection
Shrikant Malviya, Pablo Arnau-González, Miguel Arevalillo-Herráez +1
The rapid advancement of large language models (LLMs) has introduced new challenges in distinguishing human-written text from AI-generated content. In this work, we explored a pipe…
BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim +1
Trajectory prediction allows better decision-making in applications of autonomous vehicles or surveillance by predicting the short-term future movement of traffic agents. It is cla…
Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis +2
Pedestrian trajectory prediction aims to forecast future movements based on historical paths. Spatial-temporal (ST) methods often separately model spatial interactions among pedest…