MEDS is a dataset of 28,000 LLM personas performing high-school math tasks alongside psychometric tests and cognitive networks that capture math anxiety, self-efficacy, and confidence to support safer AI tutors.
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4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
LLMs persuade only psychologically susceptible humans on societal issues through trust in AI and emotional appeals, while both sides rely on logical fallacies in roughly one out of every six conversational turns.
Talk2AI is a new longitudinal dataset of 3,080 human-AI conversations with linked opinion-change and psychometric measures collected from 770 participants over four weeks.
CDS is a new synthetic corpus of LLM-generated texts on vaccines, disinformation, gender gaps, and STEM stereotypes, linked to persona attributes to enable bias and alignment audits.
citing papers explorer
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Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs
MEDS is a dataset of 28,000 LLM personas performing high-school math tasks alongside psychometric tests and cognitive networks that capture math anxiety, self-efficacy, and confidence to support safer AI tutors.
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LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies
LLMs persuade only psychologically susceptible humans on societal issues through trust in AI and emotional appeals, while both sides rely on logical fallacies in roughly one out of every six conversational turns.
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Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations
Talk2AI is a new longitudinal dataset of 3,080 human-AI conversations with linked opinion-change and psychometric measures collected from 770 participants over four weeks.
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Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior
CDS is a new synthetic corpus of LLM-generated texts on vaccines, disinformation, gender gaps, and STEM stereotypes, linked to persona attributes to enable bias and alignment audits.