Proposes a modular architecture for LLM-based wellbeing recommenders using explicit constraints on guidance, explanations, directness, and user control to address trust calibration, intent alignment, and consequence awareness.
What to compare? towards un- derstanding user sessions on price comparison platforms
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2026 2verdicts
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Designing Trustworthy LLM-based Wellbeing Recommendation through Controllable Interaction
Proposes a modular architecture for LLM-based wellbeing recommenders using explicit constraints on guidance, explanations, directness, and user control to address trust calibration, intent alignment, and consequence awareness.
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LensKit-Auto
LensKit-Auto is updated for compatibility with the latest LensKit, adding Tree Parzen Estimator optimization, algorithm reuse, visualization, documentation, and meta-learning dataset preparation.