430 citations · 1.3k across the 37 of their papers we have counts for
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Towards Better Document-level Relation Extraction via Iterative Inference
Liang Zhang, Jinsong Su, Yidong Chen +4
Document-level relation extraction (RE) aims to extract the relations between entities from the input document that usually containing many difficultly-predicted entity pairs whose…
Trigger-GNN: A Trigger-Based Graph Neural Network for Nested Named Entity Recognition
Yuan Sui, Fanyang Bu, Yingting Hu +2
Nested named entity recognition (NER) aims to identify the entity boundaries and recognize categories of the named entities in a complex hierarchical sentence. Some works have been…
A Masked Image Reconstruction Network for Document-level Relation Extraction
Liang Zhang, Yidong Cheng
Document-level relation extraction aims to extract relations among entities within a document. Compared with its sentence-level counterpart, Document-level relation extraction requ…
NC-DRE: Leveraging Non-entity Clue Information for Document-level Relation Extraction
Liang Zhang, Yidong Cheng
Document-level relation extraction (RE), which requires reasoning on multiple entities in different sentences to identify complex inter-sentence relations, is more challenging than…
A Densely Connected Criss-Cross Attention Network for Document-level Relation Extraction
Liang Zhang, Yidong Cheng
Document-level relation extraction (RE) aims to identify relations between two entities in a given document. Compared with its sentence-level counterpart, document-level RE require…