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Review maps 173 LLM mental health benchmarks, finds data limitations

By PulseAugur Editorial · [1 sources] ·

A systematic scoping review titled "Mental Health Benchmarks for Large Language Models" has identified and analyzed 173 benchmarks. The review found that the majority of these benchmarks utilize data from social media or are generated by LLMs themselves. Notably, only a small fraction, specifically 2%, of the reviewed benchmarks report the use of hidden test sets. AI

IMPACT Highlights limitations in current LLM mental health evaluation, suggesting a need for more robust and diverse datasets.

RANK_REASON The cluster contains an academic paper detailing a systematic review of benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Review maps 173 LLM mental health benchmarks, finds data limitations

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The cluster contains an academic paper detailing a systematic review of benchmarks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    "Mental Health Benchmarks for Large Language Models: A Systematic Scoping Review" maps 173 benchmarks. Most rely on social media or LLM-generated data; only 2%

    "Mental Health Benchmarks for Large Language Models: A Systematic Scoping Review" maps 173 benchmarks. Most rely on social media or LLM-generated data; only 2% report hidden test sets. # LLM # MentalHealth # AI https:// doi.org/10.17605/OSF.IO/CZB7V

    LINKS osf.io/czb7v

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