AI RESEARCH
CUNY at CLPsych 2026: A Pipeline Approach to Classification and Summarization of Mental Health Changes
arXiv CS.CL
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ArXi:2605.24164v1 Announce Type: new We describe our submission to the CLPsych~2026 Shared Task on capturing and characterizing mental health changes through social media timeline dynamics. To infer the dominant self-states in posts (Tasks 1.1 and 1.2), we ensemble in-context learning of three open-weight large language models using majority voting. For predicting moments of change in a timeline (Task~2), we train supervised classifiers on features derived from Task~1.1 predictions.