3 articles tagged with #user-profiling. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.
Researchers introduce SopriBench, a synthetic benchmark and Argus framework for detecting cumulative privacy leakage from social media posts. The work addresses gaps in multimodal privacy research by analyzing how scattered cues across text, images, and metadata can collectively expose sensitive user information like location and routines.
PaperFlow introduces a longitudinal framework for scientific paper recommendation that moves beyond static ranking to simulate real-world reading behavior across daily paper streams. The system profiles users, recommends papers under display constraints, and adapts to interest drift through multiple feedback signals, validated against a new benchmark of 1,200 user-day episodes and human expert evaluation.
Researchers introduce NBQ (Next-Best-Question), a conversational AI framework that dynamically profiles users by asking strategically optimized questions to maximize information gain. The system improves user profiling accuracy by up to 14% and includes QuickMatch, an efficient retrieval layer for reciprocal matching that accelerates search by 22.9x, with applications in hiring, marketplaces, and dating platforms.
