Document Summarization

22 benchmarks760 papers

Automatic Document Summarization is the task of rewriting a document into its shorter form while still retaining its important content. The most popular two paradigms are extractive approaches and abstractive approaches. Extractive approaches generate summaries by extracting parts of the original document (usually sentences), while abstractive methods may generate new words or phrases which are not in the original document.

<span class="description-source">Source: HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization </span>

Benchmarks

Document Summarization on CNN / Daily Mail

ROUGE-1ROUGE-2ROUGE-LPPL

Document Summarization on HowSumm-Step

ROUGE-1

Document Summarization on HowSumm-Method

ROUGE-1

Document Summarization on EmailSum (long)

BertSRLsumROUGE-1ROUGE-2ROUGE-L

Document Summarization on EmailSum (short)

BertSRLsumROUGE-1ROUGE-2ROUGE-L

Document Summarization on Arxiv HEP-TH citation graph

ROUGE-1

Document Summarization on BBC XSum

ROUGE-1ROUGE-2ROUGE-L

Document Summarization on WikiLingua (tr->en)

Rouge-L

Document Summarization on arXiv Summarization Dataset

Rouge-2