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cs.AI2026
Towards end-to-end LLM-based censoring-aware survival analysis
Yishu Wei, Hexin Dong, Yi Lin +3
Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are rarely used as end-to-end survival models because censoring prevents straightfor…
cs.AI2025
Enhancing Health Fact-Checking with LLM-Generated Synthetic Data
Jingze Zhang, Jiahe Qian, Yiliang Zhou +1
Fact-checking for health-related content is challenging due to the limited availability of annotated training data. In this study, we propose a synthetic data generation pipeline t…