Papers by Yuchu Qin

1 papers
MoCoKGC: Momentum Contrast Entity Encoding for Knowledge Graph Completion (2024.emnlp-main)

Copied to clipboard

Challenge: Existing approaches to knowledge graph completion have not integrated the structural attributes of knowledge graphs with the textual descriptions of entities to generate robust entity encodings.
Approach: They propose to integrate structural information from knowledge graphs with textual descriptions of entities to generate robust entity encodings.
Outcome: The proposed model improves on the standard evaluation metric, Mean Reciprocal Rank (MRR), while surpassing the current best model on the Wikidata5M dataset.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations