Fine-tuning a Spanish biomedical encoder on Gemini-generated synthetic data for multiple languages yields a bi-encoder that matches or exceeds BioBERT-ST on clinical code retrieval metrics, with further gains from cross-encoder reranking on most languages.
MedMT-Bench: Can LLMs memorize and understand long multi-turn conversations in medical scenarios?arXiv preprint arXiv:2603.23519, 2026
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MDIA, a specialty-routed 7-node multi-agent system, reports 0.6272 accuracy on 525 HealthBench Professional cases using GPT-5.4, outperforming the ChatGPT for Clinicians baseline by 3.72 points and attributing the lift to architectural components.
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Generalistic or Specific Embeddings, Which is Better? An Empirical Study on Search for Clinical Coding in Non-English Languages
Fine-tuning a Spanish biomedical encoder on Gemini-generated synthetic data for multiple languages yields a bi-encoder that matches or exceeds BioBERT-ST on clinical code retrieval metrics, with further gains from cross-encoder reranking on most languages.