Papers by Xueyi Liu

3 papers
DiFiNet: Boundary-Aware Semantic Differentiation and Filtration Network for Nested Named Entity Recognition (2024.acl-long)

Copied to clipboard

Challenge: Existing approaches to Named Entity Recognition focus on identifying non-nested entities, but there is no explicit guidance for boundary detection.
Approach: They propose a Boundary-aware Semantic Differentiation and Filtration Network for nested NER that leverages a biaffine attention mechanism to generate a span representation matrix.
Outcome: Extensive experiments on three benchmark datasets demonstrate the proposed model yields a new state-of-the-art performance.
Predicting the Unpredictable: Uncertainty-Aware Reasoning over Temporal Knowledge Graphs via Diffusion Process (2024.findings-acl)

Copied to clipboard

Challenge: Existing methods for Temporal Knowledge Graph reasoning capture indeterminacy in future events, but they are limited in capturing it.
Approach: They propose a Temporal Knowledge Graph reasoning process that denoises historical events and introduces Gaussian noise to corrupt target facts.
Outcome: Empirical results show that DiffuTKG outperforms state-of-the-art methods on four real-world datasets.
Synergetic Interaction Network with Cross-task Attention for Joint Relational Triple Extraction (2024.lrec-main)

Copied to clipboard

Challenge: Existing approaches to joint entity-relation extraction are limited in their ability to capture the interdependence between the two sub-tasks.
Approach: They propose a synergistic approach to capture interdependence between named entity recognition and relation extraction sub-tasks in a Synergetic Interaction Network.
Outcome: The proposed model achieves significantly better performance on three benchmark datasets.

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