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Found 8 papers, 8 papers with code
OpenAsp: A Benchmark for Multi-document Open Aspect-based Summarization
To advance research on more realistic scenarios, we introduce OpenAsp, a benchmark for multi-document \textit{open} aspect-based summarization.
Controlled Text Reduction
Producing a reduced version of a source text, as in generic or focused summarization, inherently involves two distinct subtasks: deciding on targeted content and generating a coherent text conveying it.
How "Multi" is Multi-Document Summarization?
To that end, we propose an automated measure for evaluating the degree to which a summary is ``disperse'', in the sense of the number of source documents needed to cover its content.
Proposition-Level Clustering for Multi-Document Summarization
Text clustering methods were traditionally incorporated into multi-document summarization (MDS) as a means for coping with considerable information repetition.
Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations
NLP models that compare or consolidate information across multiple documents often struggle when challenged with recognizing substantial information redundancies across the texts.
QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions
Multi-text applications, such as multi-document summarization, are typically required to model redundancies across related texts.
iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration
We introduce iFacetSum, a web application for exploring topical document sets.
Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline
Aligning sentences in a reference summary with their counterparts in source documents was shown as a useful auxiliary summarization task, notably for generating training data for salience detection.
