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Entity Embeddings

Entity Embeddings is a technique for applying deep learning to tabular data. It involves representing the categorical data of an information systems entity with multiple dimensions.

Papers

Showing 110 of 151 papers

TitleStatusHype
RaTEScore: A Metric for Radiology Report GenerationCode4
OmniSearchSage: Multi-Task Multi-Entity Embeddings for Pinterest SearchCode2
Scalable Zero-shot Entity Linking with Dense Entity RetrievalCode2
MMEAD: MS MARCO Entity Annotations and DisambiguationsCode1
AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language ModelsCode1
BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge GraphsCode1
InGram: Inductive Knowledge Graph Embedding via Relation GraphsCode1
Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph EmbeddingCode1
Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question AnsweringCode1
StarGraph: Knowledge Representation Learning based on Incomplete Two-hop SubgraphCode1
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