Introduces ToM-PD task and ToM-BPD dataset plus TTBYS dual-knowledge framework, with Qwen3-8B outperforming GPT-5 on desire, belief, and strategy prediction.
arXiv preprint arXiv:2504.08754 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
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Hesitator is a theory-grounded simulator that separates utility-based item selection from overload-aware commitment decisions to reduce unrealistic high acceptance rates in conversational recommender evaluations.
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Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents
Introduces ToM-PD task and ToM-BPD dataset plus TTBYS dual-knowledge framework, with Qwen3-8B outperforming GPT-5 on desire, belief, and strategy prediction.
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Decision-aware User Simulation Agent for Evaluating Conversational Recommender Systems
Hesitator is a theory-grounded simulator that separates utility-based item selection from overload-aware commitment decisions to reduce unrealistic high acceptance rates in conversational recommender evaluations.