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arXiv · 2509.09470

AEGIS: An Agent for Extraction and Geographic Identification in Scholarly Proceedings

Om Vishesh·Harshad Khadilkar·Deepak Akkil
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Abstract

Keeping pace with the rapid growth of academia literature presents a significant challenge for researchers, funding bodies, and academic societies. To address the time-consuming manual effort required for scholarly discovery, we present a novel, fully automated system that transitions from data discovery to direct action. Our pipeline demonstrates how a specialized AI agent, 'Agent-E', can be tasked with identifying papers from specific geographic regions within conference proceedings and then executing a Robotic Process Automation (RPA) to complete a predefined action, such as submitting a nomination form. We validated our system on 586 papers from five different conferences, where it successfully identified every target paper with a recall of 100% and a near perfect accuracy of 99.4%. This demonstration highlights the potential of task-oriented AI agents to not only filter information but also to actively participate in and accelerate the workflows of the academic community.

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Om Vishesh, Harshad Khadilkar, Deepak Akkil. 2025-09-11. AEGIS: An Agent for Extraction and Geographic Identification in Scholarly Proceedings. https://arxiv.org/abs/2509.09470

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