--- title: "Summarization — papers, page 2" description: "Summarization: 115 papers of the Elamur Research library · page 2 of 5, the most cited first. Shortening a document or a set of documents to what matters." canonical: "https://research.elamur.ai/free/en/topics/summarization/page/2/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/summarization/page/2/) [home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Summarization](https://md.research.elamur.ai/free/en/topics/summarization/) / page 2 # 📝 Summarization 115 papers · page 2 of 5 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/) Shortening a document or a set of documents to what matters. [← prev](https://md.research.elamur.ai/free/en/topics/summarization/) [1](https://md.research.elamur.ai/free/en/topics/summarization/) **2** [3](https://md.research.elamur.ai/free/en/topics/summarization/page/3/) [4](https://md.research.elamur.ai/free/en/topics/summarization/page/4/) [5](https://md.research.elamur.ai/free/en/topics/summarization/page/5/) [next →](https://md.research.elamur.ai/free/en/topics/summarization/page/3/) - [Neural Document Summarization by Jointly Learning to Score and Select Sentences](https://md.research.elamur.ai/free/en/papers/zhou-2018-neural-document-summarization-jointly-learning/) — Qingyu Zhou, Nan Yang, Furu Wei, et al. · 2018 · 446 citations - [Deep Communicating Agents for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/celikyilmaz-2018-deep-communicating-agents-abstractive-summarization/) — Asli Celikyilmaz, Antoine Bosselut, Xiaodong He, et al. · 2018 · 431 citations - [Controllable Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/fan-2018-controllable-abstractive-summarization/) — Angela Fan, David Grangier, Michael Auli · 2018 · 423 citations - [Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics](https://md.research.elamur.ai/free/en/papers/pagnoni-2021-understanding-factuality-abstractive-summarization-frank/) — Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov · 2021 · 417 citations - [Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization](https://md.research.elamur.ai/free/en/papers/barzilay-2004-catching-drift-probabilistic-content-models/) — Regina Barzilay, Lillian Lee · 2004 · 411 citations - [Abstractive Document Summarization with a Graph-Based Attentional Neural Model](https://md.research.elamur.ai/free/en/papers/tan-2017-abstractive-document-summarization-graph-based/) — Jiwei Tan, Xiaojun Wan, Jianguo Xiao · 2017 · 407 citations - [MEAD - A Platform for Multidocument Multilingual Text Summarization](https://md.research.elamur.ai/free/en/papers/radev-2004-mead-platform-multidocument-multilingual-text/) — Dragomir Radev, Timothy Allison, Sasha Blair-Goldensohn, et al. · 2004 · 400 citations - [QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization](https://md.research.elamur.ai/free/en/papers/zhong-2021-qmsum-new-benchmark-query-based/) — Ming Zhong, Da Yin, Tao Yu, et al. · 2021 · 397 citations - [Discourse-Aware Neural Extractive Text Summarization](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/) — Jiacheng Xu, Zhe Gan, Yu Cheng, et al. · 2019 · 382 citations - [A Scalable Global Model for Summarization](https://md.research.elamur.ai/free/en/papers/gillick-2009-scalable-global-model-summarization/) — Dan Gillick, Benoit Favre · 2009 · 376 citations - [Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://md.research.elamur.ai/free/en/papers/wang-2020-heterogeneous-graph-neural-networks-extractive/) — Danqing Wang, Pengfei Liu, Yining Zheng, et al. · 2020 · 368 citations - [BRIO: Bringing Order to Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2022-brio-bringing-order-abstractive-summarization/) — Yixin Liu, Pengfei Liu, Dragomir Radev, et al. · 2022 · 357 citations - [QuestEval: Summarization Asks for Fact-based Evaluation](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/) — Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al. · 2021 · 353 citations - [FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/) — Esin Durmus, He He, Mona Diab · 2020 · 350 citations - [Graph-based Neural Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/yasunaga-2017-graph-based-neural-multi-document/) — Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, et al. · 2017 · 346 citations - [SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2021-simcls-simple-framework-contrastive-learning/) — Yixin Liu, Pengfei Liu · 2021 · 340 citations - [Toward Abstractive Summarization Using Semantic Representations](https://md.research.elamur.ai/free/en/papers/liu-2015-abstractive-summarization-semantic-representations/) — Fei Liu, Jeffrey Flanigan, Sam Thomson, et al. · 2015 · 337 citations - [A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss](https://md.research.elamur.ai/free/en/papers/hsu-2018-unified-model-extractive-abstractive-summarization/) — Wan-Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, et al. · 2018 · 335 citations - [Efficient Attentions for Long Document Summarization](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/) — Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al. · 2021 · 334 citations - [GSum: A General Framework for Guided Neural Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/) — Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, et al. · 2021 · 317 citations - [Generating Wikipedia by Summarizing Long Sequences](https://md.research.elamur.ai/free/en/papers/liu-2018-generating-wikipedia-summarizing-long-sequences/) — Peter J. Liu, Mohammad Saleh, Etienne Pot, et al. · 2018 · 308 citations - [DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://md.research.elamur.ai/free/en/papers/chen-2021-dialogsum-real-life-scenario-dialogue/) — Yulong Chen, Yang Liu, Liang Chen, et al. · 2021 · 301 citations - [QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization](https://md.research.elamur.ai/free/en/papers/fabbri-2022-qafacteval-improved-qa-based-factual/) — Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al. · 2022 · 288 citations - [Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/narayan-2018-ranking-sentences-extractive-summarization-reinforcement/) — Shashi Narayan, Shay B. Cohen, Mirella Lapata · 2018 · 279 citations - [WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/ladhak-2020-wikilingua-new-benchmark-dataset-cross/) — Faisal Ladhak, Esin Durmus, Claire Cardie, et al. · 2020 · 272 citations [← prev](https://md.research.elamur.ai/free/en/topics/summarization/) [1](https://md.research.elamur.ai/free/en/topics/summarization/) **2** [3](https://md.research.elamur.ai/free/en/topics/summarization/page/3/) [4](https://md.research.elamur.ai/free/en/topics/summarization/page/4/) [5](https://md.research.elamur.ai/free/en/topics/summarization/page/5/) [next →](https://md.research.elamur.ai/free/en/topics/summarization/page/3/)