Haihua Chen

Dissecting Neuro-Symbolic Quality Assurance for Synthetic Oncology Data Generation

Synthetic clinical data generation with large language models addresses the scarcity that limits cancer staging research, but oncology hallucinations are categorically harmful: one clinically impossible staging assignment contaminates every downstream model trained on it. Neuro-symbolic pipelines validate during genera...

Defensible but Not Owned: Evidence of Agency Erosion in Agentic AI-Assisted Argumentation A Pilot Study from a Multi-Stage Policy-Writing Simulation

Quality-aware multi-source data fusion and enhancement for Medical Concept Normalization using Large Language Models.

This study finds that existing MCN benchmarks present data quality issues and underexplored data fusion potential, and data quality enhancement and LLM-based controlled-variety data augmentation help alleviate overlapping phrases and long-tail issues.