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Research questionHow can live-streaming risk detectors connect recurring behavior across sessions without sacrificing real-time response?Harmful behavior in live streams may emerge gradually and recur across seemingly unrelated sessions. Detectors that assess sessions independently can miss these dispersed patterns, while incorporating broader history can threaten timely response.
AI
Information Retrieval
Machine Learning
Retrieval-Augmented Generation
Small / On-device Models
Technology
Latest papersRecent research connected to this question, newest first.Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk AssessmentThe source describes CS-VAR, which uses retrieved cross-session behavioral evidence and LLM-guided training to help a lightweight domain-specific model perform session-level risk inference. Evidence includes offline experiments on large-scale industrial datasets and online validation, with localized signals intended to support moderation; the supplied abstract does not specify the exact risk labels, retrieval permissions, or deployment latency.research paper · Sep 3, 2026
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