Introduces APV framework and Bayesian PIIE to evaluate and enhance LLMs' reasoning about pedagogical intent, reporting strong discrimination and r=0.958 human correlation on instructional tasks.
Michael Tomasello, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll
2 Pith papers cite this work. Polarity classification is still indexing.
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A3M integrates adaptive DRL, adversarial opponent modeling, and multi-objective rewards to cut regret 30-40% versus baselines while remaining robust to strategy shifts in repeated auctions.
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Beyond Skepticism: Evaluating LLMs Pedagogical Intent Reasoning with the Adaptive Pedagogical Vigilance Framework
Introduces APV framework and Bayesian PIIE to evaluate and enhance LLMs' reasoning about pedagogical intent, reporting strong discrimination and r=0.958 human correlation on instructional tasks.
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A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions
A3M integrates adaptive DRL, adversarial opponent modeling, and multi-objective rewards to cut regret 30-40% versus baselines while remaining robust to strategy shifts in repeated auctions.