---
title: "Who cites Text Summarization with Pretrained Encoders"
description: "542 papers of the Elamur Research library cite «Text Summarization with Pretrained Encoders», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Text Summarization with Pretrained Encoders](https://md.research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/) / cited by

# Who cites «Text Summarization with Pretrained Encoders»

542 papers of our library cite it (of the 149,439 whose bibliographies we read) · 58 with a page here, the most cited first · [← back to «Text Summarization with Pretrained Encoders»](https://md.research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/)

1. **[BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://md.research.elamur.ai/free/en/papers/lewis-2020-bart-denoising-sequence-sequence-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mike Lewis, Yinhan Liu, Naman Goyal, et al.*2020 · 12,856 citations*
2. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
3. **[GLM: General Language Model Pretraining with Autoregressive Blank Infilling](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,455 citations*
4. **[Evaluating the Factual Consistency of Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/kryscinski-2020-evaluating-factual-consistency-abstractive-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wojciech Kryscinski, Bryan McCann, Caiming Xiong, et al.*2020 · 1,120 citations*
5. **[Big Bird: Transformers for Longer Sequences](https://md.research.elamur.ai/free/en/papers/zaheer-2020-big-bird-transformers-longer-sequences/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Manzil Zaheer, Guru Guruganesh, Avinava Dubey, et al.*2020 · 1,023 citations*
6. [**BARTScore: Evaluating Generated Text as Text Generation arXiv:2106.11520**Weizhe Yuan, Graham Neubig, Pengfei Liu*2021 · 815 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2021-bartscore-evaluating-generated-text-text/)
7. **[Extractive Summarization as Text Matching](https://md.research.elamur.ai/free/en/papers/zhong-2020-extractive-summarization-as-text-matching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhong, Pengfei Liu, Yiran Chen, et al.*2020 · 570 citations*
8. **[ProphetNet: Predicting Future N-gram for Sequence-to-SequencePre-training](https://md.research.elamur.ai/free/en/papers/qi-2020-prophetnet-predicting-future-n-gram/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weizhen Qi, Yu Yan, Yeyun Gong, et al.*2020 · 453 citations*
9. **[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/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Artidoro Pagnoni, Vidhisha Balachandran, Yulia Tsvetkov*2021 · 420 citations*
10. **[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/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ming Zhong, Da Yin, Tao Yu, et al.*2021 · 404 citations*
11. [**UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training arXiv:2002.12804**Hangbo Bao, Li Dong, Furu Wei, et al.*2020 · 395 citations*](https://md.research.elamur.ai/free/en/papers/bao-2020-unilmv2-pseudo-masked-language-models/)
12. **[Discourse-Aware Neural Extractive Text Summarization](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiacheng Xu, Zhe Gan, Yu Cheng, et al.*2019 · 385 citations*
13. **[Heterogeneous Graph Neural Networks for Extractive Document Summarization](https://md.research.elamur.ai/free/en/papers/wang-2020-heterogeneous-graph-neural-networks-extractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danqing Wang, Pengfei Liu, Yining Zheng, et al.*2020 · 370 citations*
14. **[BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 362 citations*
15. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Esin Durmus, He He, Mona Diab*2020 · 359 citations*
16. **[Efficient Attentions for Long Document Summarization](https://md.research.elamur.ai/free/en/papers/huang-2021-efficient-attentions-long-document-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Luyang Huang, Shuyang Cao, Nikolaus Parulian, et al.*2021 · 336 citations*
17. **[GSum: A General Framework for Guided Neural Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/dou-2021-gsum-general-framework-guided-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi, et al.*2021 · 322 citations*
18. **[Explainable Automated Fact-Checking for Public Health Claims](https://md.research.elamur.ai/free/en/papers/kotonya-2020-explainable-automated-fact-checking-public/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Neema Kotonya, Francesca Toni*2020 · 314 citations*
19. **[DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://md.research.elamur.ai/free/en/papers/chen-2021-dialogsum-real-life-scenario-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulong Chen, Yang Liu, Liang Chen, et al.*2021 · 301 citations*
20. **[QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization](https://md.research.elamur.ai/free/en/papers/fabbri-2022-qafacteval-improved-qa-based-factual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 292 citations*
21. **[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/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Faisal Ladhak, Esin Durmus, Claire Cardie, et al.*2020 · 275 citations*
22. **[TLDR: Extreme Summarization of Scientific Documents](https://md.research.elamur.ai/free/en/papers/cachola-2020-tldr-extreme-summarization-scientific-documents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Isabel Cachola, Kyle Lo, Arman Cohan, et al.*2020 · 262 citations*
23. **[CLIFF: Contrastive Learning for Improving Faithfulness and Factuality in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2021-cliff-contrastive-learning-improving-faithfulness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shuyang Cao, Lu Wang*2021 · 260 citations*
24. **[Re-evaluating Evaluation in Text Summarization](https://md.research.elamur.ai/free/en/papers/bhandari-2020-re-evaluating-evaluation-text-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Manik Bhandari, Pranav Narayan Gour, Atabak Ashfaq, et al.*2020 · 259 citations*
25. **[Generating Fact Checking Explanations](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 220 citations*
26. **[Factual Error Correction for Abstractive Summarization Models](https://md.research.elamur.ai/free/en/papers/cao-2020-factual-error-correction-abstractive-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Meng Cao, Yue Dong, Jiapeng Wu, et al.*2020 · 219 citations*
27. [**Recursively Summarizing Books with Human Feedback arXiv:2109.10862**Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.*2021 · 208 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-recursively-summarizing-books-human-feedback/)
28. **[PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization](https://md.research.elamur.ai/free/en/papers/xiao-2022-primera-pyramid-based-masked-sentence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Xiao, Iz Beltagy, Giuseppe Carenini, et al.*2022 · 205 citations*
29. **[Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization](https://md.research.elamur.ai/free/en/papers/chen-2020-multi-view-sequence-sequence-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaao Chen, Diyi Yang*2020 · 204 citations*
30. **[ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/xiao-2020-ernie-gen-enhanced-multi/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Dongling Xiao, Han Zhang, Yukun Li, et al.*2020 · 163 citations*
31. **[Multi-Fact Correction in Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/dong-2020-multi-fact-correction-abstractive-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yue Dong, Shuohang Wang, Zhe Gan, et al.*2020 · 163 citations*
32. [**ChatGPT as a Factual Inconsistency Evaluator for Text Summarization arXiv:2303.15621**Zheheng Luo, Qianqian Xie, Sophia Ananiadou*2023 · 161 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-chatgpt-factual-inconsistency-evaluator-text/)
33. **[PyMT5: multi-mode translation of natural language and Python code with transformers](https://md.research.elamur.ai/free/en/papers/clement-2020-pymt5-multi-mode-translation-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Colin Clement, Dawn Drain, Jonathan Timcheck, et al.*2020 · 158 citations*
34. **[Reducing Quantity Hallucinations in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/zhao-2020-reducing-quantity-hallucinations-abstractive-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheng Zhao, Shay B. Cohen, Bonnie Webber*2020 · 157 citations*
35. **[Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection](https://md.research.elamur.ai/free/en/papers/chen-2021-improving-faithfulness-abstractive-summarization-contrast/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sihao Chen, Fan Zhang, Kazoo Sone, et al.*2021 · 151 citations*
36. **[Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles](https://md.research.elamur.ai/free/en/papers/lu-2020-multi-xscience-large-scale-dataset/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yao Lu, Yue Dong, Laurent Charlin*2020 · 148 citations*
37. **[What Have We Achieved on Text Summarization?](https://md.research.elamur.ai/free/en/papers/huang-2020-what-have-we-achieved-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dandan Huang, Leyang Cui, Sen Yang, et al.*2020 · 143 citations*
38. **[Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs](https://md.research.elamur.ai/free/en/papers/chen-2021-structure-aware-abstractive-conversation-summarization/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jiaao Chen, Diyi Yang*2021 · 135 citations*
39. **[Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors](https://md.research.elamur.ai/free/en/papers/tang-2023-understanding-factual-errors-summarization-errors/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liyan Tang, Tanya Goyal, Alex Fabbri, et al.*2023 · 126 citations*
40. **[MLSUM: The Multilingual Summarization Corpus](https://md.research.elamur.ai/free/en/papers/scialom-2020-mlsum-multilingual-summarization-corpus/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2020 · 115 citations*
41. **[Aspect-Controllable Opinion Summarization](https://md.research.elamur.ai/free/en/papers/amplayo-2021-aspect-controllable-opinion-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reinald Kim Amplayo, Stefanos Angelidis, Mirella Lapata*2021 · 114 citations*
42. **[Truncation Sampling as Language Model Desmoothing](https://md.research.elamur.ai/free/en/papers/hewitt-2022-truncation-sampling-as-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**John Hewitt, Christopher Manning, Percy Liang*2022 · 95 citations*
43. **[Coreference-Aware Dialogue Summarization](https://md.research.elamur.ai/free/en/papers/liu-2021-coreference-aware-dialogue-summarization/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Zhengyuan Liu, Ke Shi, Nancy Chen*2021 · 81 citations*
44. **[AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/eddine-2022-arabart-pretrained-arabic-sequence-sequence/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Moussa Kamal Eddine, Nadi Tomeh, Nizar Habash, et al.*2022 · 80 citations*
45. **[Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory](https://md.research.elamur.ai/free/en/papers/cheng-2023-lift-yourself-up-retrieval-augmented/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xin Cheng, Di Luo, Xiuying Chen, et al.*2023 · 76 citations*
46. **[WikiAsp: A Dataset for Multi-domain Aspect-based Summarization](https://md.research.elamur.ai/free/en/papers/hayashi-2021-wikiasp-dataset-multi-domain-aspect/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hiroaki Hayashi, Prashant Budania, Peng Wang, et al.*2021 · 76 citations*
47. [**SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learning arXiv:2307.10234**Kiana Kheiri, Hamid Karimi*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/kheiri-2023-sentimentgpt-exploiting-gpt-advanced-sentiment/)
48. **[Extractive Summarization Considering Discourse and Coreference Relations based on Heterogeneous Graph](https://md.research.elamur.ai/free/en/papers/huang-2021-extractive-summarization-considering-discourse-coreference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yin Jou Huang, Sadao Kurohashi*2021 · 41 citations*
49. **[Top-down Discourse Parsing via Sequence Labelling](https://md.research.elamur.ai/free/en/papers/koto-2021-top-down-discourse-parsing-sequence/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Fajri Koto, Jey Han Lau, Timothy Baldwin*2021 · 37 citations*
50. **[Controllable Summarization with Constrained Markov Decision Process](https://md.research.elamur.ai/free/en/papers/chan-2021-controllable-summarization-constrained-markov-decision/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hou Pong Chan, Lu Wang, Irwin King*2021 · 34 citations*
51. [**BERT Fine-tuning For Arabic Text Summarization arXiv:2004.14135**Khalid N. Elmadani, Mukhtar Elgezouli, Anas Showk*2020 · 29 citations*](https://md.research.elamur.ai/free/en/papers/elmadani-2020-bert-fine-tuning-arabic-text/)
52. **[Modeling Local Contexts for Joint Dialogue Act Recognition and Sentiment Classification with Bi-channel Dynamic Convolutions](https://md.research.elamur.ai/free/en/papers/li-2020-modeling-local-contexts-joint-dialogue/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jingye Li, Hao Fei, Donghong Ji*2020 · 25 citations*
53. **[Cross-lingual Fine-tuning for Abstractive Arabic Text Summarization](https://md.research.elamur.ai/free/en/papers/kahla-2021-cross-lingual-fine-tuning-abstractive/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Mram Kahla, Zijian Győző Yang, Attila Novák*2021 · 18 citations*
54. **[Contextualized Embeddings for Connective Disambiguation in Shallow Discourse Parsing](https://md.research.elamur.ai/free/en/papers/knaebel-2020-contextualized-embeddings-connective-disambiguation-shallow/) [Workshop on Computational Approaches to Discourse (CODI)](https://md.research.elamur.ai/free/en/venues/codi/)**René Knaebel, Manfred Stede*2020 · 15 citations*
55. **[A Multi-Task Dataset for Assessing Discourse Coherence in Chinese Essays: Structure, Theme, and Logic Analysis](https://md.research.elamur.ai/free/en/papers/wu-2023-multi-task-dataset-assessing-discourse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongyi Wu, Xinshu Shen, Man Lan, et al.*2023 · 12 citations*
56. **[Steering into New Embedding Spaces: Analyzing Cross-Lingual Alignment Induced by Model Interventions in Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/sundar-2025-steering-into-new-embedding-spaces/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anirudh Sundar, Sinead Williamson, Katherine Metcalf, et al.*2025 · 9 citations*
57. **[Reference-Free Evaluation of Taxonomies](https://md.research.elamur.ai/free/en/papers/wullschleger-2026-reference-free-evaluation-taxonomies/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pascal Wullschleger, Majid Zarharan, Donnacha Daly, et al.*2026 · 1 citation*
58. **[Budget-Aware Routing for Long Clinical Text](https://md.research.elamur.ai/free/en/papers/qureshi-2026-budget-aware-routing-long-clinical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Khizar Qureshi, Geoffrey Martin, Yifan Peng*2026*

484 more papers of our library cite it; they have no page here yet.

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