2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2024
On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations
Shiao Meng, Xuming Hu, Aiwei Liu +4
Driven by the demand for cross-sentence and large-scale relation extraction, document-level relation extraction (DocRE) has attracted increasing research interest. Despite the cont…
cs.CL2023★ 2 cited
Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction
Xuming Hu, Junzhe Chen, Aiwei Liu +3
How can we better extract entities and relations from text? Using multimodal extraction with images and text obtains more signals for entities and relations, and aligns them throug…
cs.CL2023
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction
Shiao Meng, Xuming Hu, Aiwei Liu +4
How to identify semantic relations among entities in a document when only a few labeled documents are available? Few-shot document-level relation extraction (FSDLRE) is crucial for…