Papers by Zhenbin Chen

1 papers
MMUIE: Massive Multi-Domain Universal Information Extraction for Long Documents (2026.findings-eacl)

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Challenge: Existing document-level information extraction systems operate at the sentence level or within narrow domains due to annotation constraints.
Approach: They propose a large-scale universal dataset for multi-domain, document-level information extraction from long texts.
Outcome: The proposed dataset integrates traditional knowledge bases with large language models to extract fine-grained entities, aliases, and relation triples across 34 domains.

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