1 citations · 1 across the 4 of their papers we have counts for
9 papers
CLoE: Expert Consistency Learning for Robust Missing Modality Segmentation
Xinyu Tong, Meihua Zhou, Bowu Fan +1
Multimodal medical image segmentation often faces missing modalities at inference, which induces disagreement among modality experts and makes fusion unstable, particularly on smal…
ReStyle-TTS: Relative and Continuous Style Control for Zero-Shot Speech Synthesis
Haitao Li, Chunxiang Jin, Chenglin Li +3
Zero-shot text-to-speech models can clone a speaker's timbre from a short reference audio, but they also strongly inherit the speaking style present in the reference. As a result,…
Translating Electrocardiograms to Cardiac Magnetic Resonance Imaging Useful for Cardiac Assessment and Disease Screening: A Multi-Center Study
Zhengyao Ding, Ziyu Li, Yujian Hu +17
Cardiovascular diseases (CVDs) are the leading cause of global mortality, necessitating accessible and accurate diagnostic tools. While cardiac magnetic resonance imaging (CMR) pro…
STCTS: Generative Semantic Compression for Ultra-Low Bitrate Speech via Explicit Text-Prosody-Timbre Decomposition
Siyu Wang, Haitao Li, Donglai Zhu
Voice communication in bandwidth-constrained environments--maritime, satellite, and tactical networks--remains prohibitively expensive. Traditional codecs struggle below 1 kbps, wh…
anyECG-chat: A Generalist ECG-MLLM for Flexible ECG Input and Multi-Task Understanding
Haitao Li, Ziyu Li, Yiheng Mao +3
The advent of multimodal large language models (MLLMs) has sparked interest in their application to electrocardiogram (ECG) analysis. However, existing ECG-focused MLLMs primarily…
Fine-grained Contrastive Learning for ECG-Report Alignment with Waveform Enhancement
Haitao Li, Che Liu, Zhengyao Ding +3
Electrocardiograms (ECGs) are essential for diagnosing cardiovascular diseases. However, existing ECG-Report contrastive learning methods focus on whole-ECG and report alignment, m…