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Sagan

Paper

Supervised Fine-tuning with Synthetic Rationale Data Hurts Real-World Disease Prediction

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AI summary

arXiv:2606. 10279v1 Announce Type: new Abstract: 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 predict but why.