Jiexia Ye — accepted AI-conference papers

2026

MedSpaformer: A Transferable Transformer with Multi-Granularity Token Sparsification for Medical Time Series Classification

Jiexia Ye, Weiqi Zhang, Ziyue Li, Jia Li, Fugee Tsung

AAAI 2026technical

Accurate medical time series (MedTS) classification is essential for effective clinical diagnosis, yet remains challenging due to complex multi-channel temporal dependencies, information redundancy, and label scarcity. While transformer-based models have shown promise in time series analysis, most a

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2025

MedualTime: A Dual-Adapter Language Model for Medical Time Series-Text Multimodal Learning

Jiexia Ye, Weiqi Zhang, Ziyue Li, Jia Li, Meng Zhao, Fugee Tsung

IJCAI 2025

The recent rapid advancements in language models (LMs) have garnered attention in medical time series-text multimodal learning. However, existing contrastive learning-based and prompt-based LM approaches tend to be biased, often assigning a primary role to time series modality while treating text mo

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