# Contextual Networks and Unsupervised Ranking of Sentences

arXiv: https://arxiv.org/abs/2203.04459 · HTML: https://mlsanity.com/paper/2203.04459/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 26 references that are in the map.
- First posted on arXiv 9 Mar 2022.

## Builds on (most cited first, 11 of 11)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://mlsanity.com/paper/1808.08745/) (2018)
- [Get To The Point: Summarization with Pointer-Generator Networks](https://mlsanity.com/paper/1704.04368/) (2017)
- [Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond](https://mlsanity.com/paper/1602.06023/) (2016)
- [Extractive Summarization as Text Matching](https://mlsanity.com/paper/2004.08795/) (2020)
- [Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://mlsanity.com/paper/1802.08636/) (2018)
- [Fine-tune BERT for Extractive Summarization](https://mlsanity.com/paper/1903.10318/) (2019)
- [Sentence Centrality Revisited for Unsupervised Summarization](https://mlsanity.com/paper/1906.03508/) (2019)
- [Leveraging BERT for Extractive Text Summarization on Lectures](https://mlsanity.com/paper/1906.04165/) (2019)
- [An Unsupervised Semantic Sentence Ranking Scheme for Text Documents](https://mlsanity.com/paper/2005.02158/) (2020)

## Built on by (most cited first, 4 of 4)

- [Content Significance Distribution of Sub-Text Blocks in Articles and Its Application to Article-Organization Assessment](https://mlsanity.com/paper/2311.01673/) (2023)
- [Tag-Set-Sequence Learning for Generating Question-Answer Pairs](https://mlsanity.com/paper/2210.11608/) (2022)
- [Intrinsic Evaluation of RAG Systems for Deep-Logic Questions](https://mlsanity.com/paper/2410.02932/) (2024)
- [Constructing Cloze Questions Generatively](https://mlsanity.com/paper/2410.04266/) (2024)

## Abstract (arXiv)

We construct a contextual network to represent a document with syntactic and semantic relations between word-sentence pairs, based on which we devise an unsupervised algorithm called CNATAR (Contextual Network And Text Analysis Rank) to score sentences, and rank them through a bi-objective 0-1 knapsack maximization problem over topic analysis and sentence scores. We show that CNATAR outperforms the combined ranking of the three human judges provided on the SummBank dataset under both ROUGE and BLEU metrics, which in term significantly outperforms each individual judge's ranking. Moreover, CNATAR produces so far the highest ROUGE scores over DUC-02, and outperforms previous supervised algorithms on the CNN/DailyMail and NYT datasets. We also compare the performance of CNATAR and the latest supervised neural-network summarization models and compute oracle results.