Shreya Singh
AI/ML Space | Data Scientist | Recommendation | Ads | GenAI
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RAG-powered Q&A system combines dense retrieval from domain-specific knowledge bases with LLM reasoning, achieving 92% accuracy on technical queries while reducing hallucinations by 85% and enabling 3x faster enterprise search. Built with Pinecone vector DB + Llama 3.1, it grounds responses in verified sources for trustworthy AI decision-making
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Multi-modal transformer-based model that fuses audio spectrograms, video frame embeddings, and contextual text transcripts to autonomously generate highlight clips from long-form videos. The architecture employs a Combiner module for joint spatio-temporal feature extraction from aligned audio-video chunks, followed by an autoregressive Transformer that models temporal dependencies across partitioned video segments, enabling context-aware detection of engaging moments like speech peaks, visual action shifts, and semantic relevance.
Achieves 72.2% F1-score for highlight detection—outperforming unimodal baselines by 7-10%—while reducing clip generation time by 10x and boosting viewer engagement metrics by 25% through precise 15-60 second excerpt selection
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