Balancing Chain-of-Thought and Answer Supervision for Small Language Models on Medical Question Answering
arXiv:2611.03948v1 Announce Type: new Abstract: Small language models (<=9B parameters) can support local medical question answering (QA) while reducing privacy and latency concerns, but effective fine-tuning remains challenging. This paper compares two chain-of-thought (CoT) supervised fine-tuning
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Quelle: arXiv cs.CL (arXiv cs.CL). Original öffnen