Yongquan Jiang — accepted AI-conference papers

2025

Exploring Temporal Event Cues for Dense Video Captioning in Cyclic Co-Learning

Zhuyang Xie, Yan Yang, Yankai Yu, Jie Wang, Yongquan Jiang, Xiao Wu

AAAI 2025technical

Dense video captioning aims to detect and describe all events in untrimmed videos. This paper presents a dense video captioning network called Multi-Concept Cyclic Learning (MCCL), which aims to: (1) detect multiple concepts at the frame level and leverage these concepts to provide temporal event cu…

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2024

GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation

Guikun Xu, Yongquan Jiang, PengChuan Lei, Yan Yang, Jim Chen

ICLR 2024spotlight

The ground-state conformation of a molecule is often decisive for its properties. However, experimental or computational methods, such as density functional theory (DFT), are time-consuming and labor-intensive for obtaining this conformation. Deep learning (DL) based molecular representation learnin…

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