TEA Nets extracts agents, events, and targets from text to reveal emotional and semantic patterns in conspiracy theories and psychotherapy transcripts from humans and LLMs.
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Analyzing intermediate reasoning in LLMs reveals substantially more mental health stigma than MCQ evaluations by using clinical categories to tag and rate problematic statements.
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The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text
TEA Nets extracts agents, events, and targets from text to reveal emotional and semantic patterns in conspiracy theories and psychotherapy transcripts from humans and LLMs.
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Analyzing LLM Reasoning to Uncover Mental Health Stigma
Analyzing intermediate reasoning in LLMs reveals substantially more mental health stigma than MCQ evaluations by using clinical categories to tag and rate problematic statements.