3 papers
cs.LG2026
TWIN-MoE: Two-stage Intra-Expert Imputation Network for Incomplete Multimodal Learning
Liang Nathan Zheng, Jiyuan Liu, Wenhao Liang +3
Recent Mixture-of-Experts (MoE) approaches address missing modalities either by routing each missingness pattern to a dedicated expert, which scales poorly as the number of modalit…
cs.LG2026
Before Fusion, Ask What to Keep: Contextual Calibration of Multimodal Signals
Jiyuan Liu, Liangwei Nathan Zheng, Wei Emma Zhang +2
Multimodal systems often benefit from combining information across language, sound, and visual streams, but this benefit is not guaranteed. A modality that is useful for one input…
cs.CL2025
HopWeaver: Cross-Document Synthesis of High-Quality and Authentic Multi-Hop Questions
Zhiyu Shen, Jiyuan Liu, Yunhe Pang +3
Multi-Hop Question Answering (MHQA) is crucial for evaluating the model's capability to integrate information from diverse sources. However, creating extensive and high-quality MHQ…