10 citations · 19 across the 4 of their papers we have counts for
4 papers
Multimodal Integrated Knowledge Transfer to Large Language Models through Preference Optimization with Biomedical Applications
Zhanliang Wang, Da Wu, Quan Nguyen +2
The scarcity of high-quality multimodal biomedical data limits the ability to effectively fine-tune pretrained Large Language Models (LLMs) for specialized biomedical tasks. To add…
Integrating Chain-of-Thought and Retrieval Augmented Generation Enhances Rare Disease Diagnosis from Clinical Notes
Zhanliang Wang, Da Wu, Quan Nguyen +1
Background: Several studies show that large language models (LLMs) struggle with phenotype-driven gene prioritization for rare diseases. These studies typically use Human Phenotype…
GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Text
Da Wu, Zhanliang Wang, Hongzhuo Chen +12
Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic tests over a prolonged period of time,…
Exploring the Reversal Curse and Other Deductive Logical Reasoning in BERT and GPT-Based Large Language Models
Da Wu, Jingye Yang, Kai Wang
The term "Reversal Curse" refers to the scenario where auto-regressive decoder large language models (LLMs), such as ChatGPT, trained on "A is B" fail to learn "B is A," assuming t…