most citedCombining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization

4 citations · 4 across the 2 of their papers we have counts for

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cs.CL2026

Text Summarization With Graph Attention Networks

Mohammadreza Ardestani, Yllias Chali

This study aimed to leverage graph information, particularly Rhetorical Structure Theory (RST) and Co-reference (Coref) graphs, to enhance the performance of our baseline summariza…

cs.CL2022★ 4 cited

Combining State-of-the-Art Models with Maximal Marginal Relevance for Few-Shot and Zero-Shot Multi-Document Summarization

David Adams, Gandharv Suri, Yllias Chali

In Natural Language Processing, multi-document summarization (MDS) poses many challenges to researchers above those posed by single-document summarization (SDS). These challenges i…