EXCEEDS: New Framework and Dataset for Event Extraction in Scientific Documents
Researchers have developed EXCEEDS, an end-to-end framework for extracting complex events from scientific documents, along with SciEvents, a large-scale dataset of 2,508 documents containing 24,381 annotated events. The work addresses gaps in event extraction research by tailoring methods to the scientific domain's characteristics of dense information and complex event structures. The framework and dataset have been accepted for presentation at ACL 2026 and are being released publicly to support future research.
A research team has introduced EXCEEDS, a novel event extraction framework designed specifically for scientific documents, alongside SciEvents, a comprehensive dataset created through multi-stage manual annotation and quality control. The framework encodes dense information nuggets into a grid matrix, transforming complex event extraction into a nugget-based grid modeling task. The SciEvents dataset comprises 2,508 documents with 24,381 events organized under a schema tailored to scientific domain characteristics, particularly addressing the challenge of denser nuggets and more complex information forms compared to other domains like news and finance. Experimental results demonstrate state-of-the-art performance on the new dataset. Both the dataset and framework are being released publicly to facilitate future research in scientific event extraction.
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- arXiv cs.CLCenter
EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain
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