Master's StudentI am currently a second-year master's student at the University of Electronic Science and Technology of China (UESTC), under the supervision of Prof. Fan Zhou, Prof. Ting Zhong, and Prof. Jin Wu. My research interests lie in multimodal learning and social media analytics, where I aim to explore innovative solutions to complex challenges.
I am enthusiastic about learning and highly committed to conducting rigorous research. My ultimate goal is to contribute meaningful and impactful work to the academic and professional communities.
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University of Electronic Science and Technology of ChinaScholar of Information and Software Engineering
Master's StudentSep. 2023 - present -
University of Electronic Science and Technology of ChinaB.S. in Software EngineeringSep. 2019 - Jul. 2023
Experience
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SZ DJI Technology Co., Ltd.Embedded Engineer InternJan. 2022 - Jul. 2022
Honors & Awards
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Master's Student Academic Scholarship (2nd Division)2024
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Master's Student Academic Scholarship (1st Division)2023
Selected Publications (view all )
Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning
Rongpei Hong, Jian Lang, Jin Xu, Zhangtao Cheng, Ting Zhong, Fan Zhou
The ACM Web Conference (WWW) 2025 Full Paper Poster
The rapid spread of rumor content on online micro-video platforms poses significant threats to public health and safety. However, existing Micro-Video Rumor Detection (MVRD) methods are generally black-box, which lacks transparency and makes it difficult to understand the reasoning behind classification decisions...
Following Clues, Approaching the Truth: Explainable Micro-Video Rumor Detection via Chain-of-Thought Reasoning
Rongpei Hong, Jian Lang, Jin Xu, Zhangtao Cheng, Ting Zhong, Fan Zhou
The ACM Web Conference (WWW) 2025 Full Paper Poster
The rapid spread of rumor content on online micro-video platforms poses significant threats to public health and safety. However, existing Micro-Video Rumor Detection (MVRD) methods are generally black-box, which lacks transparency and makes it difficult to understand the reasoning behind classification decisions...
Biting Off More Than You Can Detect: Retrieval-Augmented Multimodal Experts for Short Video Hate Detection
Jian Lang, Rongpei Hong, Jin Xu, Yili Li, Xovee Xu, Fan Zhou
The ACM Web Conference (WWW) 2025 Full Paper Poster
Short Video Hate Detection (SVHD) is increasingly vital as hateful content — such as racial and gender-based discrimination — spreads rapidly across platforms like TikTok, YouTube Shorts, and Instagram Reels. Existing approaches face significant challenges:...
Biting Off More Than You Can Detect: Retrieval-Augmented Multimodal Experts for Short Video Hate Detection
Jian Lang, Rongpei Hong, Jin Xu, Yili Li, Xovee Xu, Fan Zhou
The ACM Web Conference (WWW) 2025 Full Paper Poster
Short Video Hate Detection (SVHD) is increasingly vital as hateful content — such as racial and gender-based discrimination — spreads rapidly across platforms like TikTok, YouTube Shorts, and Instagram Reels. Existing approaches face significant challenges:...
Simplifying Temporal Heterogeneous Network for Continuous-Time Link Prediction
Ce Li, Rongpei Hong, Xovee Xu, Goce Trajcevski, Fan Zhou
The ACM Conference on Information and Knowledge Management (CIKM) 2023 Full Paper
Temporal heterogeneous networks (THNs) investigate the structural interactions and their evolution over time in graphs with multiple types of nodes or edges. Existing THNs describe evolving networks as a sequence of graph snapshots and adopt mechanisms from static heterogeneous networks to capture the spatial-temporal correlation...
Simplifying Temporal Heterogeneous Network for Continuous-Time Link Prediction
Ce Li, Rongpei Hong, Xovee Xu, Goce Trajcevski, Fan Zhou
The ACM Conference on Information and Knowledge Management (CIKM) 2023 Full Paper
Temporal heterogeneous networks (THNs) investigate the structural interactions and their evolution over time in graphs with multiple types of nodes or edges. Existing THNs describe evolving networks as a sequence of graph snapshots and adopt mechanisms from static heterogeneous networks to capture the spatial-temporal correlation...