QA-guided reasoning via a separate model producing structured traces improves faithfulness, informativeness, and grounding in character description generation from books over long-context LLM baselines.
arXiv preprint arXiv:2502.12477 (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
Large-scale data from an AI platform confirms students have consistent learning rates (IQR 7.01-8.25 opportunities to 80% mastery) despite variable starting knowledge, replicating prior findings with automated knowledge components.
citing papers explorer
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Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books
QA-guided reasoning via a separate model producing structured traces improves faithfulness, informativeness, and grounding in character description generation from books over long-context LLM baselines.
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Personalized AI Practice Replicates Learning Rate Regularity at Scale
Large-scale data from an AI platform confirms students have consistent learning rates (IQR 7.01-8.25 opportunities to 80% mastery) despite variable starting knowledge, replicating prior findings with automated knowledge components.