Search Results for author: Junying Chen

Found 26 papers, 21 papers with code

On the Compositional Generalization of Multimodal LLMs for Medical Imaging

1 code implementation28 Dec 2024 Zhenyang Cai, Junying Chen, Rongsheng Wang, Weihong Wang, Yonglin Deng, Dingjie Song, Yize Chen, Zixu Zhang, Benyou Wang

Multimodal large language models (MLLMs) hold significant potential in the medical field, but their capabilities are often limited by insufficient data in certain medical domains, highlighting the need for understanding what kinds of images can be used by MLLMs for generalization.

HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs

1 code implementation25 Dec 2024 Junying Chen, Zhenyang Cai, Ke Ji, Xidong Wang, Wanlong Liu, Rongsheng Wang, Jianye Hou, Benyou Wang

To address this, we propose verifiable medical problems with a medical verifier to check the correctness of model outputs.

Reinforcement Learning (RL)

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

no code implementations16 Dec 2024 Jianqing Zhu, Huang Huang, Zhihang Lin, Juhao Liang, Zhengyang Tang, Khalid Almubarak, Abdulmohsen Alharthik, Bang An, Juncai He, Xiangbo Wu, Fei Yu, Junying Chen, Zhuoheng Ma, Yuhao Du, He Zhang, Emad A. Alghamdi, Lian Zhang, Ruoyu Sun, Haizhou Li, Benyou Wang, Jinchao Xu

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 state-of-the-art offerings like GPT-4 or ChatGPT 3. 5, due to a predominant focus on mainstream languages (e. g., English and Chinese).

CoD, Towards an Interpretable Medical Agent using Chain of Diagnosis

1 code implementation18 Jul 2024 Junying Chen, Chi Gui, Anningzhe Gao, Ke Ji, Xidong Wang, Xiang Wan, Benyou Wang

This study introduces Chain-of-Diagnosis (CoD) to enhance the interpretability of LLM-based medical diagnostics.

Decision Making Medical Diagnosis

LLMs for Doctors: Leveraging Medical LLMs to Assist Doctors, Not Replace Them

no code implementations26 Jun 2024 Wenya Xie, Qingying Xiao, Yu Zheng, Xidong Wang, Junying Chen, Ke Ji, Anningzhe Gao, Xiang Wan, Feng Jiang, Benyou Wang

Based on this, we construct a Chinese medical dataset called DoctorFLAN to support the entire workflow of doctors, which includes 92K Q\&A samples from 22 tasks and 27 specialists.

LLMs Could Autonomously Learn Without External Supervision

1 code implementation2 Jun 2024 Ke Ji, Junying Chen, Anningzhe Gao, Wenya Xie, Xiang Wan, Benyou Wang

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 that is both labor-intensive and inherently limited.

ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models

1 code implementation18 Feb 2024 Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, Junying Chen, Xiangbo Wu, Zhiyi Zhang, Zhihong Chen, Jianquan Li, Xiang Wan, Benyou Wang

Large vision-language models (LVLMs) have shown premise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities.

Language Modelling Question Answering +1

MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria

1 code implementation23 Nov 2023 Wentao Ge, Shunian Chen, Guiming Hardy Chen, Junying Chen, Zhihong Chen, Nuo Chen, Wenya Xie, Shuo Yan, Chenghao Zhu, Ziyue Lin, Song Dingjie, Xidong Wang, Anningzhe Gao, Zhang Zhiyi, Jianquan Li, Xiang Wan, Benyou Wang

To this end, in our paper, we propose a new evaluation paradigm for MLLMs, which is evaluating MLLMs with per-sample criteria using potent MLLM as the judge.

HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs

1 code implementation16 Nov 2023 Junying Chen, Xidong Wang, Ke Ji, Anningzhe Gao, Feng Jiang, Shunian Chen, Hongbo Zhang, Dingjie Song, Wenya Xie, Chuyi Kong, Jianquan Li, Xiang Wan, Haizhou Li, Benyou Wang

We validate the new protocol in the domains where proprietary LLMs like ChatGPT perform relatively poorly, such as Traditional Chinese Medicine.

Domain Adaptation Language Modeling +1

AceGPT, Localizing Large Language Models in Arabic

1 code implementation21 Sep 2023 Huang Huang, Fei Yu, Jianqing Zhu, Xuening Sun, Hao Cheng, Dingjie Song, Zhihong Chen, Abdulmohsen Alharthi, Bang An, Juncai He, Ziche Liu, Zhiyi Zhang, Junying Chen, Jianquan Li, Benyou Wang, Lian Zhang, Ruoyu Sun, Xiang Wan, Haizhou Li, Jinchao Xu

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 addressed by current mainstream models.

Instruction Following Language Modeling +3

Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense Retrieval

1 code implementation19 Sep 2023 Nengzheng Jin, Dongfang Li, Junying Chen, Joanna Siebert, Qingcai Chen

Open-domain table question answering aims to provide answers to a question by retrieving and extracting information from a large collection of tables.

Question Answering Table Retrieval +2

Spinal nerve segmentation method and dataset construction in endoscopic surgical scenarios

1 code implementation20 Jul 2023 Shaowu Peng, Pengcheng Zhao, Yongyu Ye, Junying Chen, Yunbing Chang, Xiaoqing Zheng

Endoscopic surgery is currently an important treatment method in the field of spinal surgery and avoiding damage to the spinal nerves through video guidance is a key challenge.

Segmentation Semantic Segmentation

HuatuoGPT, towards Taming Language Model to Be a Doctor

2 code implementations24 May 2023 Hongbo Zhang, Junying Chen, Feng Jiang, Fei Yu, Zhihong Chen, Jianquan Li, Guiming Chen, Xiangbo Wu, Zhiyi Zhang, Qingying Xiao, Xiang Wan, Benyou Wang, Haizhou Li

Experimental results demonstrate that HuatuoGPT achieves state-of-the-art results in performing medical consultation among open-source LLMs in GPT-4 evaluation, human evaluation, and medical benchmark datasets.

Language Modeling Language Modelling +1

SeDR: Segment Representation Learning for Long Documents Dense Retrieval

1 code implementation20 Nov 2022 Junying Chen, Qingcai Chen, Dongfang Li, Yutao Huang

In SeDR, Segment-Interaction Transformer is proposed to encode long documents into document-aware and segment-sensitive representations, while it holds the complexity of splitting-and-pooling and outperforms other segment-interaction patterns on DR.

Representation Learning Retrieval

Diaformer: Automatic Diagnosis via Symptoms Sequence Generation

1 code implementation20 Dec 2021 Junying Chen, Dongfang Li, Qingcai Chen, Wenxiu Zhou, Xin Liu

Detailed analysis on symptom inquiry prediction demonstrates that the potential of applying symptoms sequence generation for automatic diagnosis.

Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise

no code implementations26 May 2021 Jiajia Li, Peihua Feng, Liang Zhao, Junying Chen, Mengmeng Du, Yangyang Yu, Jian Song, Ying Wu

Our simulation results show that the increase of the IP3 noise intensity induces the depolarization-block epileptic seizures together with an increase in neuronal firing frequency.

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning

1 code implementation19 Mar 2021 Zhigang Dai, Bolun Cai, Yugeng Lin, Junying Chen

To fully utilize the label annotations, we propose Unified Momentum Contrast (UniMoCo), which extends MoCo to support arbitrary ratios of labeled data and unlabeled data training.

Representation Learning

MedWriter: Knowledge-Aware Medical Text Generation

no code implementations COLING 2020 Youcheng Pan, Qingcai Chen, Weihua Peng, Xiaolong Wang, Baotian Hu, Xin Liu, Junying Chen, Wenxiu Zhou

To exploit the domain knowledge to guarantee the correctness of generated text has been a hot topic in recent years, especially for high professional domains such as medical.

Text Generation

UP-DETR: Unsupervised Pre-training for Object Detection with Transformers

2 code implementations CVPR 2021 Zhigang Dai, Bolun Cai, Yugeng Lin, Junying Chen

DEtection TRansformer (DETR) for object detection reaches competitive performance compared with Faster R-CNN via a transformer encoder-decoder architecture.

Decoder Multi-Task Learning +4

Cannot find the paper you are looking for? You can Submit a new open access paper.