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ESLM: Improving entity summarization by leveraging language models
Published on 2024-05-2877 Views
Entity summarizers for knowledge graphs are crucial in various applications. Achieving high performance on the task of entity summarization is hence critical for many applications based on knowledge g
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Presentation
ESLM: Improving Entity Summarization by Leveraging Language Models00:00
Entity Summarization Challenge00:21
Entity Summarization Overview01:27
Motivation02:21
Problem Statement03:28
Related Work04:40
Entity Summarization Using Language Models05:44
Formally definition05:59
Experiment Setup08:05
Comparison with state-of-the-art approaches (F-Measure)08:55
Comparison with state-of-the-art approaches09:46
ESLM is well aligned with the ground truth summary10:20
ESLM provides a wide range of information on the target entity11:23
Highest F-measure performance of BERT, ERNIE, and T5 on ESLM11:57
Highest NDCG scores of BERT, ERNIE, and T5 on ESLM12:57
Conclusion and Future Work13:23
Thank you!14:44