most citedShizhenGPT: Towards Multimodal LLMs for Traditional Chinese Medicine

3 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

eess.SP2025

WaveMind: Towards a Conversational EEG Foundation Model Aligned to Textual and Visual Modalities

Ziyi Zeng, Zhenyang Cai, Yixi Cai +8

Electroencephalography (EEG) interpretation using multimodal large language models (MLLMs) offers a novel approach for analyzing brain signals. However, the complex nature of brain…

cs.CL2025

EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs

Yuhao Zhang, Yuhao Du, Zhanchen Dai +4

Speech-to-speech large language models (SLLMs) are attracting increasing attention. Derived from text-based large language models (LLMs), SLLMs often exhibit degradation in knowled…

cs.CL20253 cited

ShizhenGPT: Towards Multimodal LLMs for Traditional Chinese Medicine

Junying Chen, Zhenyang Cai, Zhiheng Liu +10

Despite the success of large language models (LLMs) in various domains, their potential in Traditional Chinese Medicine (TCM) remains largely underexplored due to two critical barr…

cs.CL2025

Soundwave: Less is More for Speech-Text Alignment in LLMs

Yuhao Zhang, Zhiheng Liu, Fan Bu +3

Existing end-to-end speech large language models (LLMs) usually rely on large-scale annotated data for training, while data-efficient training has not been discussed in depth. We f…

cs.CL2024

Alignment at Pre-training! Towards Native Alignment for Arabic LLMs

Juhao Liang, Zhenyang Cai, Jianqing Zhu +9

The alignment of large language models (LLMs) is critical for developing effective and safe language models. Traditional approaches focus on aligning models during the instruction…

cs.CL2024

Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion

Jianqing Zhu, Huang Huang, Zhihang Lin +18

This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to st…