activity
20172024
most citedSummary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models

765 citations · 1.6k across the 46 of their papers we have counts for

collaborators

46 papers

q-bio.NC2024

Brain Dialogue Interface (BDI): A User-Friendly fMRI Model for Interactive Brain Decoding

Heng Huang, Lin Zhao, Zihao Wu +5

Brain decoding techniques are essential for understanding the neurocognitive system. Although numerous methods have been introduced in this field, accurately aligning complex exter…

cs.CV2024★ 2 cited

Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning

Chong Ma, Hanqi Jiang, Wenting Chen +10

In the medical multi-modal frameworks, the alignment of cross-modality features presents a significant challenge. However, existing works have learned features that are implicitly…

eess.IV2023★ 12 cited

Holistic Evaluation of GPT-4V for Biomedical Imaging

Zhengliang Liu, Hanqi Jiang, Tianyang Zhong +47

In this paper, we present a large-scale evaluation probing GPT-4V's capabilities and limitations for biomedical image analysis. GPT-4V represents a breakthrough in artificial gener…

cs.CL2023★ 18 cited

PolicyGPT: Automated Analysis of Privacy Policies with Large Language Models

Chenhao Tang, Zhengliang Liu, Chong Ma +8

Privacy policies serve as the primary conduit through which online service providers inform users about their data collection and usage procedures. However, in a bid to be comprehe…

physics.med-ph2023

Artificial General Intelligence for Radiation Oncology

Chenbin Liu, Zhengliang Liu, Jason Holmes +14

The emergence of artificial general intelligence (AGI) is transforming radiation oncology. As prominent vanguards of AGI, large language models (LLMs) such as GPT-4 and PaLM 2 can…

physics.med-ph2023★ 11 cited

RadOnc-GPT: A Large Language Model for Radiation Oncology

Zhengliang Liu, Peilong Wang, Yiwei Li +12

This paper presents RadOnc-GPT, a large language model specialized for radiation oncology through advanced tuning methods. RadOnc-GPT was finetuned on a large dataset of radiation…

cs.CL2023★ 30 cited

Radiology-Llama2: Best-in-Class Large Language Model for Radiology

Zhengliang Liu, Yiwei Li, Peng Shu +18

This paper introduces Radiology-Llama2, a large language model specialized for radiology through a process known as instruction tuning. Radiology-Llama2 is based on the Llama2 arch…

q-bio.NC2023

Robust Core-Periphery Constrained Transformer for Domain Adaptation

Xiaowei Yu, Zeyu Zhang, Dajiang Zhu +1

Unsupervised domain adaptation (UDA) aims to learn transferable representation across domains. Recently a few UDA works have successfully applied Transformer-based methods and achi…

cs.CV2023★ 3 cited

Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification

Haixing Dai, Lu Zhang, Lin Zhao +9

With the popularity of deep neural networks (DNNs), model interpretability is becoming a critical concern. Many approaches have been developed to tackle the problem through post-ho…

eess.AS2023★ 7 cited

Exploring Multimodal Approaches for Alzheimer's Disease Detection Using Patient Speech Transcript and Audio Data

Hongmin Cai, Xiaoke Huang, Zhengliang Liu +8

Alzheimer's disease (AD) is a common form of dementia that severely impacts patient health. As AD impairs the patient's language understanding and expression ability, the speech of…

eess.IV2023★ 13 cited

Segment Anything Model (SAM) for Radiation Oncology

Lian Zhang, Zhengliang Liu, Lu Zhang +10

In this study, we evaluate the performance of the Segment Anything Model (SAM) in clinical radiotherapy. Our results indicate that SAM's 'segment anything' mode can achieve clinica…

cs.LG2023

Identification of Causal Relationship between Amyloid-beta Accumulation and Alzheimer's Disease Progression via Counterfactual Inference

Haixing Dai, Mengxuan Hu, Qing Li +12

Alzheimer's disease (AD) is a neurodegenerative disorder that is beginning with amyloidosis, followed by neuronal loss and deterioration in structure, function, and cognition. The…

cs.CV2023★ 12 cited

Review of Large Vision Models and Visual Prompt Engineering

Jiaqi Wang, Zhengliang Liu, Lin Zhao +18

Visual prompt engineering is a fundamental technology in the field of visual and image Artificial General Intelligence, serving as a key component for achieving zero-shot capabilit…

cs.CL2023★ 19 cited

Evaluating Large Language Models for Radiology Natural Language Processing

Zhengliang Liu, Tianyang Zhong, Yiwei Li +43

The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…

cs.CV2023★ 26 cited

SAMAug: Point Prompt Augmentation for Segment Anything Model

Haixing Dai, Chong Ma, Zhiling Yan +14

This paper introduces SAMAug, a novel visual point augmentation method for the Segment Anything Model (SAM) that enhances interactive image segmentation performance. SAMAug generat…

cs.CL2023★ 15 cited

AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology

Haixing Dai, Yiwei Li, Zhengliang Liu +14

In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which…

cs.CL2023★ 21 cited

Radiology-GPT: A Large Language Model for Radiology

Zhengliang Liu, Aoxiao Zhong, Yiwei Li +17

We introduce Radiology-GPT, a large language model for radiology. Using an instruction tuning approach on an extensive dataset of radiology domain knowledge, Radiology-GPT demonstr…

cs.AI2023★ 44 cited

Artificial General Intelligence for Medical Imaging Analysis

Xiang Li, Lin Zhao, Lu Zhang +16

Large-scale Artificial General Intelligence (AGI) models, including Large Language Models (LLMs) such as ChatGPT/GPT-4, have achieved unprecedented success in a variety of general…

cs.CV2023★ 7 cited

Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT

Zhenxiang Xiao, Yuzhong Chen, Lu Zhang +14

Prompts have been proven to play a crucial role in large language models, and in recent years, vision models have also been using prompts to improve scalability for multiple downst…

cs.CL2023★ 79 cited

Differentiate ChatGPT-generated and Human-written Medical Texts

Wenxiong Liao, Zhengliang Liu, Haixing Dai +8

Background: Large language models such as ChatGPT are capable of generating grammatically perfect and human-like text content, and a large number of ChatGPT-generated texts have ap…

cs.CL2023★ 9 cited

ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT

Tianyang Zhong, Yaonai Wei, Li Yang +13

Large language models (LLMs) such as ChatGPT have recently demonstrated significant potential in mathematical abilities, providing valuable reasoning paradigm consistent with human…

cs.CL2023★ 14 cited

Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task

Zihao Wu, Lu Zhang, Chao Cao +12

Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capabili…

cs.AI2023★ 10 cited

AGI for Agriculture

Guoyu Lu, Sheng Li, Gengchen Mai +11

Artificial General Intelligence (AGI) is poised to revolutionize a variety of sectors, including healthcare, finance, transportation, and education. Within healthcare, AGI is being…

cs.AI2023★ 118 cited

Prompt Engineering for Healthcare: Methodologies and Applications

Jiaqi Wang, Enze Shi, Sigang Yu +21

Prompt engineering is a critical technique in the field of natural language processing that involves designing and optimizing the prompts used to input information into models, aim…