LLM responses mirror venting with higher regulation and escalation; therapist personas lower escalation while preserving regulation, and lay raters miss escalation.
A Computational Framework for Behavioral Assessment of LLM Therapists , publisher =
4 Pith papers cite this work, alongside 18 external citations. Polarity classification is still indexing.
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In an AI-simulated peer support setting, mental health professionals consistently identified missed distress cues and premature advice-giving in peer supporters' responses, revealing a systematic gap between peer and professional standards.
Mainstream conversational models show escalating affective misalignments and ethical guidance failures during staged emotional trajectories, organized into a taxonomy of interactional breakdowns.
Generative AI should be evaluated through computational hermeneutics using iterative, human-inclusive benchmarks that measure cultural context rather than isolated model outputs.
citing papers explorer
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When Support Escalates Distress: Regulation and Escalation in LLM Responses to Venting and Advice-Seeking
LLM responses mirror venting with higher regulation and escalation; therapist personas lower escalation while preserving regulation, and lay raters miss escalation.
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"Is This Really a Human Peer Supporter?": Misalignments Between Peer Supporters and Experts in LLM-Supported Interactions
In an AI-simulated peer support setting, mental health professionals consistently identified missed distress cues and premature advice-giving in peer supporters' responses, revealing a systematic gap between peer and professional standards.
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Breakdowns in Conversational AI: Interactional Failures in Emotionally and Ethically Sensitive Contexts
Mainstream conversational models show escalating affective misalignments and ethical guidance failures during staged emotional trajectories, organized into a taxonomy of interactional breakdowns.
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Computational Hermeneutics: Evaluating generative AI as a cultural technology
Generative AI should be evaluated through computational hermeneutics using iterative, human-inclusive benchmarks that measure cultural context rather than isolated model outputs.