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

arXiv: https://arxiv.org/abs/2509.09470 · HTML: https://mlsanity.com/paper/2509.09470/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 5 references that are in the map.
- First posted on arXiv 11 Sep 2025.

## Built on by (most cited first, 1 of 1)

- [EpiBench: Benchmarking Multi-turn Research Workflows for Multimodal Agents](https://mlsanity.com/paper/2604.05557/) (2026)

## Abstract (arXiv)

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.