68 citations · 115 across the 16 of their papers we have counts for
6 papers · 1 filter
Multimodal Representation Learning of Cardiovascular Magnetic Resonance Imaging
Jielin Qiu, Peide Huang, Makiya Nakashima +10
Self-supervised learning is crucial for clinical imaging applications, given the lack of explicit labels in healthcare. However, conventional approaches that rely on precise vision…
Align and Attend: Multimodal Summarization with Dual Contrastive Losses
Bo He, Jun Wang, Jielin Qiu +3
The goal of multimodal summarization is to extract the most important information from different modalities to form output summaries. Unlike the unimodal summarization, the multimo…
Benchmarking Robustness of Multimodal Image-Text Models under Distribution Shift
Jielin Qiu, Yi Zhu, Xingjian Shi +5
Multimodal image-text models have shown remarkable performance in the past few years. However, evaluating robustness against distribution shifts is crucial before adopting them in…
LiveSeg: Unsupervised Multimodal Temporal Segmentation of Long Livestream Videos
Jielin Qiu, Franck Dernoncourt, Trung Bui +3
Livestream videos have become a significant part of online learning, where design, digital marketing, creative painting, and other skills are taught by experienced experts in the s…
Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment
Jielin Qiu, Jiacheng Zhu, Mengdi Xu +6
Multimedia summarization with multimodal output (MSMO) is a recently explored application in language grounding. It plays an essential role in real-world applications, i.e., automa…
MHMS: Multimodal Hierarchical Multimedia Summarization
Jielin Qiu, Jiacheng Zhu, Mengdi Xu +6
Multimedia summarization with multimodal output can play an essential role in real-world applications, i.e., automatically generating cover images and titles for news articles or p…