Papers by Hazem Abou Hamdan
GraphLSS: Integrating Lexical, Structural, and Semantic Features for Long Document Extractive Summarization (2025.naacl-short)
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| Challenge: | Graph-based methods for extracting documents have been popular, but they often require external tools or additional machine learning models to define graph components. |
| Approach: | They propose a heterogeneous graph construction for extractive summarization that defines two levels of information and four types of edges without any need for auxiliary learning models. |
| Outcome: | The proposed graph construction outperforms previous graph-based models on two datasets and is available on GitHub. |