Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Retrieval from out-of-domain foundation models enables personalization of a lightweight transformer for stress detection, yielding +3.92% accuracy and +4.76% F1 gains on WESAD without user labels.
citing papers explorer
-
Before You Scroll Again: Predicting Regretful Social Media Sessions from In-the-Wild Contextual and Wearable Sensing
Intention-use gaps and displacement of valued activities predict social media regret more strongly than duration, with pre-session context generalizing across users and physiological signals adding person-specific predictive power.
-
Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection
Retrieval from out-of-domain foundation models enables personalization of a lightweight transformer for stress detection, yielding +3.92% accuracy and +4.76% F1 gains on WESAD without user labels.