Papers by Jiatan Huang

2 papers
Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Prediction (2026.findings-acl)

Copied to clipboard

Challenge: Existing approaches to ground large language models in external knowledge are limited by hallucinations and a lack of granular medical context.
Approach: They propose a framework that replaces external retrieval with internal, key-based knowledge access by encoding clinical information directly into the model’s parameter space.
Outcome: The proposed framework achieves state-of-the-art performance across four benchmark healthcare outcome prediction datasets.
RiTeK: A Dataset for Large Language Models Complex Reasoning over Textual Knowledge Graphs in Medicine (2026.findings-acl)

Copied to clipboard

Challenge: Existing methods for retrieving medical textual knowledge Graphs struggle to perform well, a study finds . existing methods struggle to provide accurate answers to complex questions, he says .
Approach: They synthesize user queries integrating diverse topological structures, relational information, and complex textual descriptions.
Outcome: a new dataset for medical textual knowledge graphs shows that existing methods struggle to perform well . main bottlenecks lie in the scarcity of existing medical TKGs and the limited expressiveness of their topological structures .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations