3 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
M2G-LLM: Enhancing Clinical Prediction via Multimodal Graph Reasoning and LLM Context Injection
Inyoung Choi, Sukwon Yun, Jiayi Xin +3
Integrating diverse data modalities --- such as clinical notes, laboratory results, and medical imaging --- is essential for advancing clinical decision-making. While Large Languag…
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts
Jiayi Xin, Sukwon Yun, Jie Peng +4
Modality fusion is a cornerstone of multimodal learning, enabling information integration from diverse data sources. However, vanilla fusion methods are limited by (1) inability to…
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer
Huaizhi Qu, Inyoung Choi, Zhen Tan +6
LLM ensembles are widely used for LLM judges. However, how to estimate their accuracy, especially in an efficient way, is unknown. In this paper, we present a principled maximum a…
Flex-MoE: Modeling Arbitrary Modality Combination via the Flexible Mixture-of-Experts
Sukwon Yun, Inyoung Choi, Jie Peng +6
Multimodal learning has gained increasing importance across various fields, offering the ability to integrate data from diverse sources such as images, text, and personalized recor…