ScrollMind

Ruyi Yang [Individual Contributor]
A controllable video recommendation system that allows users to express explicit viewing intent via natural language, dynamically overriding the default algorithmic feed.

Methods

Multimodal content understanding: video thumbnails + text features → 11-category classification with confidence scores
LLM-powered rule generation: natural language input → structured filtering rules (time slot + content type)
Intent filter injected post-recall, soft-weighting candidates before ranking
Re-ranking stage further adjusted via intent embedding to surface intent-matching content

scrollmind-full.mp4

Pipeline

Future Work

Extend to implicit intent modeling — infer user mood/context from watch behavior rather than requiring explicit input

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