
Medprompt, a run-time steering strategy, demonstrates the potential of guiding general-purpose LLMs to achieve state-of-the-art performance in specialized domains like medicine. By employing structured, multi-step prompting techniques such as chain-of-thought (CoT) reasoning, curated few-shot examples, and choice-shuffle ensembling, Medprompt bridges the gap between generalist and domain-specific models. This approach significantly enhances performance on medical benchmarks […]
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