Search Results for author: Li Cai

Found 6 papers, 3 papers with code

Using Item Response Theory to Measure Gender and Racial Bias of a BERT-based Automated English Speech Assessment System

no code implementations NAACL (BEA) 2022 Alexander Kwako, Yixin Wan, Jieyu Zhao, Kai-Wei Chang, Li Cai, Mark Hansen

This study addresses the need to examine potential biases of transformer-based models in the context of automated English speech assessment.

A Survey on Temporal Knowledge Graph: Representation Learning and Applications

no code implementations2 Mar 2024 Li Cai, Xin Mao, Yuhao Zhou, Zhaoguang Long, Changxu Wu, Man Lan

Knowledge graph representation learning aims to learn low-dimensional vector embeddings for entities and relations in a knowledge graph.

Graph Representation Learning Knowledge Graphs

Query2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphs

1 code implementation17 Oct 2023 Yao Xu, Shizhu He, Cunguang Wang, Li Cai, Kang Liu, Jun Zhao

However, these methods train KG embeddings and neural set operators concurrently on both simple (one-hop) and complex (multi-hop and logical) queries, which causes performance degradation on simple queries and low training efficiency.

Complex Query Answering

An Effective and Efficient Time-aware Entity Alignment Framework via Two-aspect Three-view Label Propagation

1 code implementation12 Jul 2023 Li Cai, Xin Mao, Youshao Xiao, Changxu Wu, Man Lan

Entity alignment (EA) aims to find the equivalent entity pairs between different knowledge graphs (KGs), which is crucial to promote knowledge fusion.

Entity Alignment Knowledge Graphs

A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs

1 code implementation COLING 2022 Li Cai, Xin Mao, Meirong Ma, Hao Yuan, Jianchao Zhu, Man Lan

However, we believe that it is not necessary to learn the embeddings of temporal information in KGs since most TKGs have uniform temporal representations.

Entity Alignment Entity Embeddings +1

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