activity
20242026
most citedShizhenGPT: Towards Multimodal LLMs for Traditional Chinese Medicine

3 citations · 5 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

What Happens Before Decoding? Prefill Determines GUI Grounding in VLMs

Jiaping Lin, Fei Shen, Junzhe Li +4

Existing training-free approaches for GUI grounding often rely on multiple inference runs, such as iterative cropping or candidate aggregation, to identify target elements. Despite…

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.CL2025★ 3 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★ 1 cited

S2S-Arena: Evaluating Paralinguistic Instruction Following in Speech-to-Speech Models

Feng Jiang, Zhiyu Lin, Yiyang Liu +6

Recent advances in large language models (LLMs) have fundamentally reshaped speech-to-speech (S2S) systems, enabling increasingly natural spoken interaction. However, existing benc…

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★ 1 cited

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…