2 papers
cs.AI2026
Supervised Fine-tuning with Synthetic Rationale Data Hurts Real-World Disease Prediction
Buxin Su, Bingxuan Li, Cheng Qian +3
Supervised fine-tuning with synthetic rationale data is widely assumed to improve language model performance on clinical prediction tasks by teaching models not just what to predic…
cs.HC2025
HEPHA: A Mixed-Initiative Image Labeling Tool for Specialized Domains
Shiyuan Zhou, Bingxuan Li, Xiyuan Chen +4
Image labeling is an important task for training computer vision models. In specialized domains, such as healthcare, it is expensive and challenging to recruit specialists for imag…