CRADLE Bench: A Clinician-Annotated Benchmark for Multi-Faceted Mental Health Crisis and Safety Risk Detection

• URL: http://arxiv.org/abs/2510.23845v1
• Date: Mon, 27 Oct 2025 20:32:38 GMT
• Title: CRADLE Bench: A Clinician-Annotated Benchmark for Multi-Faceted Mental Health Crisis and Safety Risk Detection
• Authors: Grace Byun, Rebecca Lipschutz, Sean T. Minton, Abigail Lott, Jinho D. Choi,
• Abstract summary: We introduce CRADLE BENCH, a benchmark for multi-faceted crisis detection.<n>Our benchmark provides 600 clinician-annotated evaluation examples and 420 development examples.<n>We further fine-tune six crisis detection models on subsets defined by consensus and unanimous ensemble agreement.
• Score: 8.296902072126182
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Detecting mental health crisis situations such as suicide ideation, rape, domestic violence, child abuse, and sexual harassment is a critical yet underexplored challenge for language models. When such situations arise during user--model interactions, models must reliably flag them, as failure to do so can have serious consequences. In this work, we introduce CRADLE BENCH, a benchmark for multi-faceted crisis detection. Unlike previous efforts that focus on a limited set of crisis types, our benchmark covers seven types defined in line with clinical standards and is the first to incorporate temporal labels. Our benchmark provides 600 clinician-annotated evaluation examples and 420 development examples, together with a training corpus of around 4K examples automatically labeled using a majority-vote ensemble of multiple language models, which significantly outperforms single-model annotation. We further fine-tune six crisis detection models on subsets defined by consensus and unanimous ensemble agreement, providing complementary models trained under different agreement criteria.

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