25 citations · 93 across the 35 of their papers we have counts for
38 papers
HuatuoGPT-3: RL-Only Domain Adaptation from Base Models
Junying Chen, Xinyuan Xie, Ziniu Li +7
Domain adaptation aims to turn a general-purpose large language model (LLM) into an expert for a target domain. While the dominant SFT+RL pipeline offers a convenient cold start, i…
Enabling Doctor-Centric Medical AI with LLMs through Workflow-Aligned Tasks and Benchmarks
Wenya Xie, Qingying Xiao, Yu Zheng +8
The rise of large language models (LLMs) has transformed healthcare by offering clinical guidance, yet their direct deployment to patients poses safety risks due to limited domain…
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…
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…
TalkVid: A Large-Scale Diversified Dataset for Audio-Driven Talking Head Synthesis
Shunian Chen, Hejin Huang, Yexin Liu +10
Audio-driven talking head synthesis has achieved remarkable photorealism, yet state-of-the-art (SOTA) models exhibit a critical failure: they lack generalization to the full spectr…
MedGen: Unlocking Medical Video Generation by Scaling Granularly-annotated Medical Videos
Rongsheng Wang, Junying Chen, Ke Ji +4
Recent advances in video generation have shown remarkable progress in open-domain settings, yet medical video generation remains largely underexplored. Medical videos are critical…
ShareGPT-4o-Image: Aligning Multimodal Models with GPT-4o-Level Image Generation
Junying Chen, Zhenyang Cai, Pengcheng Chen +5
Recent advances in multimodal generative models have unlocked photorealistic, instruction-aligned image generation, yet leading systems like GPT-4o-Image remain proprietary and ina…
SRLAgent: Enhancing Self-Regulated Learning Skills through Gamification and LLM Assistance
Wentao Ge, Yuqing Sun, Ziyan Wang +5
Self-regulated learning (SRL) is crucial for college students navigating increased academic demands and independence. Insufficient SRL skills can lead to disorganized study habits,…
FusionAudio-1.2M: Towards Fine-grained Audio Captioning with Multimodal Contextual Fusion
Shunian Chen, Xinyuan Xie, Zheshu Chen +5
High-quality, large-scale audio captioning is crucial for advancing audio understanding, yet current automated methods often generate captions that lack fine-grained detail and con…
The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models
Ke Ji, Jiahao Xu, Tian Liang +10
Improving the reasoning capabilities of large language models (LLMs) typically requires supervised fine-tuning with labeled data or computationally expensive sampling. We introduce…
Do LLMs Triage Like Clinicians? A Dynamic Study of Outpatient Referral
Xiaoxiao Liu, Qingying Xiao, Bingquan Zhang +8
Outpatient referral (OR) is a core clinical workflow that assigns patients to hospital departments under incomplete and evolving information, yet it is commonly simplified as a sta…
RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
Wanlong Liu, Junying Chen, Ke Ji +3
Retrieval-Augmented Generation (RAG) has emerged as a key paradigm for enhancing large language models (LLMs) by incorporating external knowledge. However, current RAG methods face…
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs
Junying Chen, Zhenyang Cai, Ke Ji +5
The breakthrough of OpenAI o1 highlights the potential of enhancing reasoning to improve LLM. Yet, most research in reasoning has focused on mathematical tasks, leaving domains lik…
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan +6
The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper,…
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…
Exploring Compositional Generalization of Multimodal LLMs for Medical Imaging
Zhenyang Cai, Junying Chen, Rongsheng Wang +6
Medical imaging provides essential visual insights for diagnosis, and multimodal large language models (MLLMs) are increasingly utilized for its analysis due to their strong genera…
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…
Both Text and Images Leaked! A Systematic Analysis of Data Contamination in Multimodal LLM
Dingjie Song, Sicheng Lai, Mingxuan Wang +3
The rapid advancement of multimodal large language models (MLLMs) has significantly enhanced performance across benchmarks. However, data contamination-unintentional memorization o…
VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment
Lei Li, Zhihui Xie, Mukai Li +7
As large vision-language models (LVLMs) evolve rapidly, the demand for high-quality and diverse data to align these models becomes increasingly crucial. However, the creation of su…
Roadmap towards Superhuman Speech Understanding using Large Language Models
Fan Bu, Yuhao Zhang, Xidong Wang +3
The success of large language models (LLMs) has prompted efforts to integrate speech and audio data, aiming to create general foundation models capable of processing both textual a…
Beyond Binary: Towards Fine-Grained LLM-Generated Text Detection via Role Recognition and Involvement Measurement
Zihao Cheng, Li Zhou, Feng Jiang +2
The rapid development of large language models (LLMs), like ChatGPT, has resulted in the widespread presence of LLM-generated content on social media platforms, raising concerns ab…
Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts
Guorui Zheng, Xidong Wang, Juhao Liang +3
Adapting medical Large Language Models to local languages can reduce barriers to accessing healthcare services, but data scarcity remains a significant challenge, particularly for…
LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture
Xidong Wang, Dingjie Song, Shunian Chen +5
Expanding the long-context capabilities of Multi-modal Large Language Models~(MLLMs) is critical for advancing video understanding and high-resolution image analysis. Achieving thi…
CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis
Junying Chen, Chi Gui, Anningzhe Gao +4
The field of medical diagnosis has undergone a significant transformation with the advent of large language models (LLMs), yet the challenges of interpretability within these model…