51 citations · 178 across the 24 of their papers we have counts for
25 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…
MedGEN-Bench: A Contextually Entangled Benchmark for Open-ended Multimodal Medical Generation
Junjie Yang, Yuhao Yan, Gang Wu +12
Medical vision-language models (VLMs) are increasingly expected to support clinical workflows through diagnostic text and relevant medical images. However, current medical visual b…
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…
PrinciplismQA: A Philosophy-Grounded Approach to Assessing LLM-Human Clinical Medical Ethics Alignment
Chang Hong, Minghao Wu, Qingying Xiao +5
As medical LLMs transition to clinical deployment, assessing their ethical reasoning capability becomes critical. While achieving high accuracy on knowledge benchmarks, LLMs lack v…
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…
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
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…
LLMs for Doctors: Leveraging Medical LLMs to Assist Doctors, Not Replace Them
Wenya Xie, Qingying Xiao, Yu Zheng +7
The recent success of Large Language Models (LLMs) has had a significant impact on the healthcare field, providing patients with medical advice, diagnostic information, and more. H…
LLMs Could Autonomously Learn Without External Supervision
Ke Ji, Junying Chen, Anningzhe Gao +3
In the quest for super-human performance, Large Language Models (LLMs) have traditionally been tethered to human-annotated datasets and predefined training objectives-a process tha…
HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale
Junying Chen, Chi Gui, Ruyi Ouyang +10
The rapid development of multimodal large language models (MLLMs), such as GPT-4V, has led to significant advancements. However, these models still face challenges in medical multi…
MileBench: Benchmarking MLLMs in Long Context
Dingjie Song, Shunian Chen, Guiming Hardy Chen +3
Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image task…
Apollo: A Lightweight Multilingual Medical LLM towards Democratizing Medical AI to 6B People
Xidong Wang, Nuo Chen, Junyin Chen +9
Despite the vast repository of global medical knowledge predominantly being in English, local languages are crucial for delivering tailored healthcare services, particularly in are…
ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models
Guiming Hardy Chen, Shunian Chen, Ruifei Zhang +7
Large vision-language models (LVLMs) have shown premise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they require…
MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria
Wentao Ge, Shunian Chen, Guiming Hardy Chen +14
Multimodal large language models (MLLMs) have broadened the scope of AI applications. Existing automatic evaluation methodologies for MLLMs are mainly limited in evaluating queries…
HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs
Junying Chen, Xidong Wang, Ke Ji +11
Adapting a language model into a specific domain, a.k.a `domain adaption', is a common practice when specialized knowledge, e.g. medicine, is not encapsulated in a general language…
AceGPT, Localizing Large Language Models in Arabic
Huang Huang, Fei Yu, Jianqing Zhu +17
This paper is devoted to the development of a localized Large Language Model (LLM) specifically for Arabic, a language imbued with unique cultural characteristics inadequately addr…
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User Simulator
Chuyi Kong, Yaxin Fan, Xiang Wan +2
The unparalleled performance of closed-sourced ChatGPT has sparked efforts towards its democratization, with notable strides made by leveraging real user and ChatGPT dialogues, as…
CMB: A Comprehensive Medical Benchmark in Chinese
Xidong Wang, Guiming Hardy Chen, Dingjie Song +8
Large Language Models (LLMs) provide a possibility to make a great breakthrough in medicine. The establishment of a standardized medical benchmark becomes a fundamental cornerstone…
On the Difference of BERT-style and CLIP-style Text Encoders
Zhihong Chen, Guiming Hardy Chen, Shizhe Diao +2
Masked language modeling (MLM) has been one of the most popular pretraining recipes in natural language processing, e.g., BERT, one of the representative models. Recently, contrast…
HuatuoGPT, towards Taming Language Model to Be a Doctor
Hongbo Zhang, Junying Chen, Feng Jiang +10
In this paper, we present HuatuoGPT, a large language model (LLM) for medical consultation. The core recipe of HuatuoGPT is to leverage both \textit{distilled data from ChatGPT} an…
Injecting Knowledge into Biomedical Pre-trained Models via Polymorphism and Synonymous Substitution
Hongbo Zhang, Xiang Wan, Benyou Wang
Pre-trained language models (PLMs) were considered to be able to store relational knowledge present in the training data. However, some relational knowledge seems to be discarded u…
Huatuo-26M, a Large-scale Chinese Medical QA Dataset
Jianquan Li, Xidong Wang, Xiangbo Wu +6
In this paper, we release a largest ever medical Question Answering (QA) dataset with 26 million QA pairs. We benchmark many existing approaches in our dataset in terms of both ret…
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
Phoenix: Democratizing ChatGPT across Languages
Zhihong Chen, Feng Jiang, Junying Chen +11
This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and…