@inproceedings{elneima-etal-2026-media,
    title = "Media-to-Insights: A Multi-Agent {AI} System for Continuous Media Monitoring, Analysis, and Reporting",
    author = "Elneima, Ashraf Hatim  and
      Yilmaz, Ozan  and
      Nasrallah, Hadi  and
      Hewavitharana, Sanjika  and
      Al-Badrashiny, Mohamed  and
      Sawaf, Hassan",
    editor = "Durrett, Greg  and
      Jian, Ping",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-demo.44/",
    pages = "445--452",
    ISBN = "979-8-89176-392-0",
    abstract = "Continuous monitoring of high-volume media streams requires systems that go beyond keyword alerts to deliver structured, actionable intelligence. We present a multi-agent media monitoring system that processes streaming articles through three stages: (1) a Matching Agent that uses a hybrid keyword-then-semantic matching approach, reducing agent invocations by 2̃0{\%} (2) a batched multi-agent feature extraction, reducing core feature-extraction calls from 7 to 2 per article - a 71{\%} reduction - with bounded quality tradeoffs; and (3) a Report Generation Agent that uses deterministic deduplication and density-based clustering. Four autonomous life-cycle agents manage the evolution of watchers."
}