activity
20222024
most citedAlign and Attend: Multimodal Summarization with Dual Contrastive Losses

2 citations · 8 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition

Jielin Qiu, William Han, Winfred Wang +6

Open-domain real-world entity recognition is essential yet challenging, involving identifying various entities in diverse environments. The lack of a suitable evaluation dataset ha…

cs.CV2024

SnapNTell: Enhancing Entity-Centric Visual Question Answering with Retrieval Augmented Multimodal LLM

Jielin Qiu, Andrea Madotto, Zhaojiang Lin +7

Vision-extended LLMs have made significant strides in Visual Question Answering (VQA). Despite these advancements, VLLMs still encounter substantial difficulties in handling querie…

cs.RO20231 cited

Embodied Executable Policy Learning with Language-based Scene Summarization

Jielin Qiu, Mengdi Xu, William Han +2

Large Language models (LLMs) have shown remarkable success in assisting robot learning tasks, i.e., complex household planning. However, the performance of pretrained LLMs heavily…

cs.CV20232 cited

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…

cs.CV20232 cited

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…

cs.CL20231 cited

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?

Jielin Qiu, William Han, Jiacheng Zhu +5

Recent advancements in Large Language Models (LLMs) have drawn increasing attention since the learned embeddings pretrained on large-scale datasets have shown powerful ability in v…