Introduces TableGrid Navigation (TGN) and Progressive Inference Prompting (PIP) as training-free structured prompting frameworks that improve LLM performance on table question answering over baselines on TableBench and achieve SOTA on FeTaQa.
The CLEAR path: A framework for enhancing information literacy through prompt engineering
2 Pith papers cite this work. Polarity classification is still indexing.
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General-purpose LLMs with advanced prompting strategies provide better support for designing pharmacoepidemiologic studies than biomedical LLMs, as shown by higher relevance and justification scores on 46 real protocols.
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Employing General-Purpose and Biomedical Large Language Models with Advanced Prompt Engineering for Pharmacoepidemiologic Study Design
General-purpose LLMs with advanced prompting strategies provide better support for designing pharmacoepidemiologic studies than biomedical LLMs, as shown by higher relevance and justification scores on 46 real protocols.