# Ranking Sentences for Extractive Summarization with Reinforcement Learning

arXiv: https://arxiv.org/abs/1802.08636 · HTML: https://mlsanity.com/paper/1802.08636/

## Key facts

- Cited by 128 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Feb 2018.

## Built on by (most cited first, 30 of 128)

- [BARTScore: Evaluating Generated Text as Text Generation](https://mlsanity.com/paper/2106.11520/) (2021)
- [Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation](https://mlsanity.com/paper/2310.18235/) (2023)
- [Advances and Challenges in Conversational Recommender Systems: A Survey](https://mlsanity.com/paper/2101.09459/) (2021)
- [Evaluating the Factual Consistency of Large Language Models Through News Summarization](https://mlsanity.com/paper/2211.08412/) (2022)
- [Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection](https://mlsanity.com/paper/2104.09061/) (2021)
- [Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback](https://mlsanity.com/paper/2306.00186/) (2023)
- [DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents](https://mlsanity.com/paper/2101.11796/) (2021)
- [Extractive Summarization via ChatGPT for Faithful Summary Generation](https://mlsanity.com/paper/2304.04193/) (2023)
- [A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models](https://mlsanity.com/paper/2406.11289/) (2024)
- [Aspect-Controllable Opinion Summarization](https://mlsanity.com/paper/2109.03171/) (2021)
- [Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles](https://mlsanity.com/paper/2309.09369/) (2023)
- [mFACE: Multilingual Summarization with Factual Consistency Evaluation](https://mlsanity.com/paper/2212.10622/) (2022)
- [Discrete Prompt Compression with Reinforcement Learning](https://mlsanity.com/paper/2308.08758/) (2023)
- [Automatic Text Evaluation through the Lens of Wasserstein Barycenters](https://mlsanity.com/paper/2108.12463/) (2021)
- [Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs](https://mlsanity.com/paper/2104.08400/) (2021)
- [DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization](https://mlsanity.com/paper/2110.08168/) (2021)
- [InfoLM: A New Metric to Evaluate Summarization & Data2Text Generation](https://mlsanity.com/paper/2112.01589/) (2021)
- [Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand](https://mlsanity.com/paper/2112.04139/) (2021)
- [Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization](https://mlsanity.com/paper/2209.03549/) (2022)
- [HEGEL: Hypergraph Transformer for Long Document Summarization](https://mlsanity.com/paper/2210.04126/) (2022)
- [Toward Unifying Text Segmentation and Long Document Summarization](https://mlsanity.com/paper/2210.16422/) (2022)
- [RefSum: Refactoring Neural Summarization](https://mlsanity.com/paper/2104.07210/) (2021)
- [DiffuSum: Generation Enhanced Extractive Summarization with Diffusion](https://mlsanity.com/paper/2305.01735/) (2023)
- [AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization](https://mlsanity.com/paper/2203.10945/) (2022)
- [Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation](https://mlsanity.com/paper/2210.07544/) (2022)
- [MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes](https://mlsanity.com/paper/2107.08929/) (2021)
- [Multiplex Graph Neural Network for Extractive Text Summarization](https://mlsanity.com/paper/2108.12870/) (2021)
- [Data Augmentation for Abstractive Query-Focused Multi-Document Summarization](https://mlsanity.com/paper/2103.01863/) (2021)
- [See, Hear, Read: Leveraging Multimodality with Guided Attention for Abstractive Text Summarization](https://mlsanity.com/paper/2105.09601/) (2021)
- [Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning](https://mlsanity.com/paper/2205.08221/) (2022)

## Abstract (arXiv)

Single document summarization is the task of producing a shorter version of a document while preserving its principal information content. In this paper we conceptualize extractive summarization as a sentence ranking task and propose a novel training algorithm which globally optimizes the ROUGE evaluation metric through a reinforcement learning objective. We use our algorithm to train a neural summarization model on the CNN and DailyMail datasets and demonstrate experimentally that it outperforms state-of-the-art extractive and abstractive systems when evaluated automatically and by humans.