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cs.LG2026
TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health
Yuang Fan, Lilin Xu, Millie Wu +8
Longitudinal passive sensing enables continuous health prediction, yet models often fail under cross-dataset distribution shifts. Traditional ML overfits cohort-specific artifacts,…
cs.LG2025
Time2Lang: Bridging Time-Series Foundation Models and Large Language Models for Health Sensing Beyond Prompting
Arvind Pillai, Dimitris Spathis, Subigya Nepal +6
Large language models (LLMs) show promise for health applications when combined with behavioral sensing data. Traditional approaches convert sensor data into text prompts, but this…