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This paper presents an LLM-based pipeline for analyzing mental health changes from sequentially ordered social media posts, participating in the CLPsych 2026 shared task. It performs post-level assessment and user-level temporal modeling to capture shifts in psychological well-being.
CUNY's submission to the CLPsych 2026 shared task uses a pipeline approach combining in-context learning with open-weight LLMs, supervised classifiers, and retrieval-augmented generation to classify and summarize mental health changes from Reddit timelines, achieving top rankings on multiple subtasks.