Automatic knowledge graph construction aims at manufacturing structured human
knowledge. To this end, much effort has historically been spent extracting informative fact …

Existing research on multimodal relation extraction (MRE) faces two co-existing challenges,
internal-information over-utilization and external-information under-exploitation. To combat …

Document-level relation extraction (DocRE) is the task of identifying all relations between
each entity pair in a document. Evidence, defined as sentences containing clues for the …

Recently, numerous efforts have continued to push up performance boundaries of document-
level relation extraction (DocRE) and have claimed significant progress in DocRE. In this …

Document-level Event Causality Identification (DECI) aims to identify causal relations
between event pairs in a document. It poses a great challenge of across-sentence reasoning …

Document-level relation extraction (RE) aims to extract relational triples from a document.
One of its primary challenges is to predict implicit relations between entities, which are not …

Document-level relation extraction (DocRE) aims to extract relations between entities in a
whole document. One of the pivotal challenges of DocRE is to capture the intricate …

Document-level Relation Extraction (DocRE), which aims to extract relations from a long
context, is a critical challenge in achieving fine-grained structural comprehension and …

Document-level relation extraction (DocRE) poses the challenge of identifying relationships
between entities within a document. Existing approaches rely on logical reasoning or …

Document-level relation extraction (RE) aims to identify relations between entities across
multiple sentences. Most previous methods focused on document-level RE under full …