Search Results for author: Ori Ernst

Found 8 papers, 8 papers with code

OpenAsp: A Benchmark for Multi-document Open Aspect-based Summarization

1 code implementation7 Dec 2023 Shmuel Amar, Liat Schiff, Ori Ernst, Asi Shefer, Ori Shapira, Ido Dagan

To advance research on more realistic scenarios, we introduce OpenAsp, a benchmark for multi-document \textit{open} aspect-based summarization.

Document Summarization Multi-Document Summarization

Controlled Text Reduction

2 code implementations24 Oct 2022 Aviv Slobodkin, Paul Roit, Eran Hirsch, Ori Ernst, Ido Dagan

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?

1 code implementation23 Oct 2022 Ruben Wolhandler, Arie Cattan, Ori Ernst, Ido Dagan

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.

Document Summarization Multi-Document Summarization

Proposition-Level Clustering for Multi-Document Summarization

2 code implementations NAACL 2022 Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, Ido Dagan

Text clustering methods were traditionally incorporated into multi-document summarization (MDS) as a means for coping with considerable information repetition.

Clustering Document Summarization +3

Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations

1 code implementation NAACL 2022 Daniela Brook Weiss, Paul Roit, Ori Ernst, Ido Dagan

NLP models that compare or consolidate information across multiple documents often struggle when challenged with recognizing substantial information redundancies across the texts.

Document Summarization Multi-Document Summarization +2

Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline

1 code implementation CoNLL (EMNLP) 2021 Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, Ido Dagan

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.

Clustering Document Summarization +1

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