Papers by Hazem Abou Hamdan

1 papers
GraphLSS: Integrating Lexical, Structural, and Semantic Features for Long Document Extractive Summarization (2025.naacl-short)

Copied to clipboard

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.

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