Small open-weight language models can self-optimize prompts for clinical named entity recognition in dental notes, reaching micro F1 of 0.864 after DPO on Qwen2.5-14B.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Self-Prompting Small Language Models for Privacy-Sensitive Clinical Information Extraction
Small open-weight language models can self-optimize prompts for clinical named entity recognition in dental notes, reaching micro F1 of 0.864 after DPO on Qwen2.5-14B.