[HTML][HTML] Summary of chatgpt-related research and perspective towards the future of large language models

Y Liu, T Han, S Ma, J Zhang, Y Yang, J Tian, H He, A Li… - Meta-Radiology, 2023 - Elsevier
This paper presents a comprehensive survey of ChatGPT-related (GPT-3.5 and GPT-4)
research, state-of-the-art large language models (LLM) from the GPT series, and their …

Foundational models defining a new era in vision: A survey and outlook

M Awais, M Naseer, S Khan, RM Anwer… - arXiv preprint arXiv …, 2023 - arxiv.org
Vision systems to see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

Mitigating object hallucinations in large vision-language models through visual contrastive decoding

S Leng, H Zhang, G Chen, X Li, S Lu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Large Vision-Language Models (LVLMs) have advanced considerably intertwining
visual recognition and language understanding to generate content that is not only coherent …

Analyzing and mitigating object hallucination in large vision-language models

Y Zhou, C Cui, J Yoon, L Zhang, Z Deng, C Finn… - arXiv preprint arXiv …, 2023 - arxiv.org
Large vision-language models (LVLMs) have shown remarkable abilities in understanding
visual information with human languages. However, LVLMs still suffer from object …

Prompt engineering for healthcare: Methodologies and applications

J Wang, E Shi, S Yu, Z Wu, C Ma, H Dai, Q Yang… - arXiv preprint arXiv …, 2023 - arxiv.org
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, aiming …

Deep transfer learning for automatic speech recognition: Towards better generalization

H Kheddar, Y Himeur, S Al-Maadeed, A Amira… - Knowledge-Based …, 2023 - Elsevier
Automatic speech recognition (ASR) has recently become an important challenge when
using deep learning (DL). It requires large-scale training datasets and high computational …

Polyp-sam: Transfer sam for polyp segmentation

Y Li, M Hu, X Yang - Medical Imaging 2024: Computer-Aided …, 2024 - spiedigitallibrary.org
Automatic segmentation of colon polyps can significantly reduce the misdiagnosis of colon
cancer and improve physician annotation efficiency. While many methods have been …

[HTML][HTML] Large language models in radiology: fundamentals, applications, ethical considerations, risks, and future directions

TA D'Antonoli, A Stanzione, C Bluethgen… - Diagnostic and …, 2024 - ncbi.nlm.nih.gov
With the advent of large language models (LLMs), the artificial intelligence revolution in
medicine and radiology is now more tangible than ever. Every day, an increasingly large …

Pre-trained multimodal large language model enhances dermatological diagnosis using SkinGPT-4

J Zhou, X He, L Sun, J Xu, X Chen, Y Chu… - Nature …, 2024 - nature.com
Large language models (LLMs) are seen to have tremendous potential in advancing
medical diagnosis recently, particularly in dermatological diagnosis, which is a very …

Challenges and barriers of using large language models (LLM) such as ChatGPT for diagnostic medicine with a focus on digital pathology–a recent scoping review

E Ullah, A Parwani, MM Baig, R Singh - Diagnostic pathology, 2024 - Springer
Background The integration of large language models (LLMs) like ChatGPT in diagnostic
medicine, with a focus on digital pathology, has garnered significant attention. However …