Search Results for author:
Found 8 papers, 1 papers with code
An Analysis for Reasoning Bias of Language Models with Small Initialization
We provide a theoretical framework from the perspective of model training dynamics to explain these phenomena.
Anchor function: a type of benchmark functions for studying language models
However, language model research faces significant challenges, especially for academic research groups with constrained resources.
Ophtha-LLaMA2: A Large Language Model for Ophthalmology
In recent years, pre-trained large language models (LLMs) have achieved tremendous success in the field of Natural Language Processing (NLP).
Holistic Evaluation of GPT-4V for Biomedical Imaging
GPT-4V represents a breakthrough in artificial general intelligence (AGI) for computer vision, with applications in the biomedical domain.
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT
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 downstream tasks.
ChatABL: Abductive Learning via Natural Language Interaction with ChatGPT
The proposed method uses the strengths of LLMs' understanding and logical reasoning to correct the incomplete logical facts for optimizing the performance of perceptual module, by summarizing and reorganizing reasoning rules represented in natural language format.
Deep image prior for undersampling high-speed photoacoustic microscopy
Photoacoustic microscopy (PAM) is an emerging imaging method combining light and sound.
Reconstructing undersampled photoacoustic microscopy images using deep learning
One primary technical challenge in photoacoustic microscopy (PAM) is the necessary compromise between spatial resolution and imaging speed.
