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Findings show that researchers leaned on GenAI to fill knowledge gaps while maintaining epistemic agency for novelty discovery, and an expertise paradox was uncovered: GenAI outputs were hardest to verify when most needed.
This study proposes a framework to automatically extract and generate task-level principles to automatically extract and generate task-level principles for data generation and evaluation, enabling controllable data creation and fine-grained, interpretable assessment of LLM capabilities.
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