---
title: "Who cites Abstractive Text Summarization — 933 citing papers"
description: "933 papers of the Elamur Research library cite «Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond», found in…"
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---
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# Who cites «Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond»

933 papers of our library cite it (of the 149,439 whose bibliographies we read) · 142 with a page here, the most cited first · page 1 of 2 · 1–100 · [← back to «Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond»](https://md.research.elamur.ai/free/en/papers/nallapati-2016-abstractive-text-summarization-sequence-sequence/)

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1. [**Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer arXiv:1910.10683**Colin Raffel, Noam Shazeer, Adam Roberts, et al.*2019 · 11,325 citations*](https://md.research.elamur.ai/free/en/papers/raffel-2019-exploring-limits-transfer-learning-unified/)
2. [**Training language models to follow instructions with human feedback arXiv:2203.02155**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 10,224 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
3. **[fairseq: A Fast, Extensible Toolkit for Sequence Modeling](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Myle Ott, Sergey Edunov, Alexei Baevski, et al.*2019 · 3,984 citations*
4. [**Convolutional Sequence to Sequence Learning arXiv:1705.03122**Jonas Gehring, Michael Auli, David Grangier, et al.*2017 · 3,042 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-sequence-sequence-learning/)
5. [**Direct Preference Optimization: Your Language Model is Secretly a Reward Model arXiv:2305.18290**Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.*2023 · 2,896 citations*](https://md.research.elamur.ai/free/en/papers/rafailov-2023-direct-preference-optimization-language-model/)
6. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
7. [**The Curious Case of Neural Text Degeneration arXiv:1904.09751**Ari Holtzman, Jan Buys, Li Du, et al.*2019 · 2,660 citations*](https://md.research.elamur.ai/free/en/papers/holtzman-2019-curious-case-neural-text-degeneration/)
8. **[OpenNMT: Open-Source Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,475 citations*
9. **[Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://md.research.elamur.ai/free/en/papers/narayan-2018-don-t-give-me-details/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 2,149 citations*
10. **[Text Summarization with Pretrained Encoders](https://md.research.elamur.ai/free/en/papers/liu-2019-text-summarization-pretrained-encoders/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Mirella Lapata*2019 · 2,095 citations*
11. [**PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization arXiv:1912.08777**Jingqing Zhang, Yao Zhao, Mohammad Saleh, et al.*2019 · 1,828 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-pegasus-pre-training-extracted-gap/)
12. [**A Deep Reinforced Model for Abstractive Summarization arXiv:1705.04304**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,657 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
13. **[SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents](https://md.research.elamur.ai/free/en/papers/nallapati-2016-summarunner-recurrent-neural-network-based/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Ramesh Nallapati, Feifei Zhai, Bowen Zhou*2016 · 1,575 citations*
14. [**CTRL: A Conditional Transformer Language Model for Controllable Generation arXiv:1909.05858**Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.*2019 · 1,291 citations*](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/)
15. **[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*
16. **[Abstractive Sentence Summarization with Attentive Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/chopra-2016-abstractive-sentence-summarization-attentive-recurrent/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sumit Chopra, Michael Auli, Alexander M. Rush*2016 · 1,094 citations*
17. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations*
18. **[GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,026 citations*
19. **[A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents](https://md.research.elamur.ai/free/en/papers/cohan-2018-discourse-aware-attention-model-abstractive/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arman Cohan, Franck Dernoncourt, Doo Soon Kim, et al.*2018 · 1,026 citations*
20. **[Bottom-Up Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/gehrmann-2018-bottom-up-abstractive-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Gehrmann, Yuntian Deng, Alexander Rush*2018 · 947 citations*
21. [**A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity arXiv:2302.04023**Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.*2023 · 882 citations*](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/)
22. **[Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting](https://md.research.elamur.ai/free/en/papers/chen-2018-fast-abstractive-summarization-reinforce-selected/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yen-Chun Chen, Mohit Bansal*2018 · 826 citations*
23. **[Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond](https://md.research.elamur.ai/free/en/papers/yang-2023-harnessing-power-llms-practice-survey/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.*2023 · 814 citations*
24. **[Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies](https://md.research.elamur.ai/free/en/papers/grusky-2018-newsroom-dataset-1-3-million/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Max Grusky, Mor Naaman, Yoav Artzi*2018 · 789 citations*
25. **[Multi-News: A Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model](https://md.research.elamur.ai/free/en/papers/fabbri-2019-multi-news-large-scale-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alexander Fabbri, Irene Li, Tianwei She, et al.*2019 · 750 citations*
26. **[SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/gliwa-2019-samsum-corpus-human-annotated-dialogue/) [Workshop on New Frontiers in Summarization](https://md.research.elamur.ai/free/en/venues/workshop-on-new-frontiers-in-summarization/)**Bogdan Gliwa, Iwona Mochol, Maciej Biesek, et al.*2019 · 715 citations*
27. **[Massive Exploration of Neural Machine Translation Architectures](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Denny Britz, Anna Goldie, Minh-Thang Luong, et al.*2017 · 574 citations*
28. **[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*
29. **[Neural Text Summarization: A Critical Evaluation](https://md.research.elamur.ai/free/en/papers/kryscinski-2019-neural-text-summarization-critical-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, et al.*2019 · 559 citations*
30. [**The Natural Language Decathlon: Multitask Learning as Question Answering arXiv:1806.08730**Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, et al.*2018 · 545 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2018-natural-language-decathlon-multitask-learning/)
31. [**Learned in Translation: Contextualized Word Vectors arXiv:1708.00107**Bryan McCann, James Bradbury, Caiming Xiong, et al.*2017 · 512 citations*](https://md.research.elamur.ai/free/en/papers/mccann-2017-learned-translation-contextualized-word-vectors/)
32. [**Large Language Models: A Survey arXiv:2402.06196**Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.*2024 · 471 citations*](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/)
33. **[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*
34. **[HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization](https://md.research.elamur.ai/free/en/papers/zhang-2019-hibert-document-level-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingxing Zhang, Furu Wei, Ming Zhou*2019 · 451 citations*
35. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Zhou, Nan Yang, Furu Wei, et al.*2018 · 450 citations*
36. **[Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/falke-2019-ranking-generated-summaries-correctness-interesting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, et al.*2019 · 445 citations*
37. [**Pay Less Attention with Lightweight and Dynamic Convolutions arXiv:1901.10430**Felix Wu, Angela Fan, Alexei Baevski, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/)
38. **[Controllable Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/fan-2018-controllable-abstractive-summarization/) [Workshop on Neural Machine Translation and Generation](https://md.research.elamur.ai/free/en/venues/workshop-on-neural-machine-translation-and-generation/)**Angela Fan, David Grangier, Michael Auli*2018 · 427 citations*
39. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiwei Tan, Xiaojun Wan, Jianguo Xiao*2017 · 409 citations*
40. **[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*
41. **[LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://md.research.elamur.ai/free/en/papers/guo-2022-longt5-efficient-text-text-transformer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mandy Guo, Joshua Ainslie, David Uthus, et al.*2022 · 399 citations*
42. **[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*
43. **[BRIO: Bringing Order to Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2022-brio-bringing-order-abstractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Liu, Pengfei Liu, Dragomir Radev, et al.*2022 · 360 citations*
44. **[QuestEval: Summarization Asks for Fact-based Evaluation](https://md.research.elamur.ai/free/en/papers/scialom-2021-questeval-summarization-asks-fact-based/) [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.*2021 · 359 citations*
45. **[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*
46. **[Graph-based Neural Multi-Document Summarization](https://md.research.elamur.ai/free/en/papers/yasunaga-2017-graph-based-neural-multi-document/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, et al.*2017 · 351 citations*
47. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Liu, Pengfei Liu*2021 · 341 citations*
48. [**Generating Wikipedia by Summarizing Long Sequences arXiv:1801.10198**Peter J. Liu, Mohammad Saleh, Etienne Pot, et al.*2018 · 334 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-generating-wikipedia-summarizing-long-sequences/)
49. **[Selective Encoding for Abstractive Sentence Summarization](https://md.research.elamur.ai/free/en/papers/zhou-2017-selective-encoding-abstractive-sentence-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Zhou, Nan Yang, Furu Wei, et al.*2017 · 330 citations*
50. **[Unsupervised Pretraining for Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/ramachandran-2017-unsupervised-pretraining-sequence-sequence-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Prajit Ramachandran, Peter Liu, Quoc Le*2017 · 327 citations*
51. **[Controlling Output Length in Neural Encoder-Decoders](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 324 citations*
52. **[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*
53. **[LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongfu Jiang, Xiang Ren, Bill Yuchen Lin*2023 · 321 citations*
54. **[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*
55. **[Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/narayan-2018-ranking-sentences-extractive-summarization-reinforcement/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 290 citations*
56. **[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*
57. **[Retrieve, Rerank and Rewrite: Soft Template Based Neural Summarization](https://md.research.elamur.ai/free/en/papers/cao-2018-retrieve-rerank-rewrite-soft-template/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqiang Cao, Wenjie Li, Sujian Li, et al.*2018 · 270 citations*
58. **[Selective Attention for Context-aware Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/maruf-2019-selective-attention-context-aware-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sameen Maruf, André F. T. Martins, Gholamreza Haffari*2019 · 263 citations*
59. **[Language as a Latent Variable: Discrete Generative Models for Sentence Compression](https://md.research.elamur.ai/free/en/papers/miao-2016-language-as-latent-variable-discrete/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yishu Miao, Phil Blunsom*2016 · 262 citations*
60. **[On Extractive and Abstractive Neural Document Summarization with Transformer Language Models](https://md.research.elamur.ai/free/en/papers/pilault-2020-extractive-abstractive-neural-document-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jonathan Pilault, Raymond Li, Sandeep Subramanian, et al.*2020 · 261 citations*
61. **[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*
62. **[Multi-Reward Reinforced Summarization with Saliency and Entailment](https://md.research.elamur.ai/free/en/papers/pasunuru-2018-multi-reward-reinforced-summarization-saliency/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ramakanth Pasunuru, Mohit Bansal*2018 · 255 citations*
63. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
64. **[Sentence Centrality Revisited for Unsupervised Summarization](https://md.research.elamur.ai/free/en/papers/zheng-2019-sentence-centrality-revisited-unsupervised-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zheng, Mirella Lapata*2019 · 251 citations*
65. **[MSMO: Multimodal Summarization with Multimodal Output](https://md.research.elamur.ai/free/en/papers/zhu-2018-msmo-multimodal-summarization-multimodal-output/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junnan Zhu, Haoran Li, Tianshang Liu, et al.*2018 · 245 citations*
66. **[Optimizing the Factual Correctness of a Summary: A Study of Summarizing Radiology Reports](https://md.research.elamur.ai/free/en/papers/zhang-2020-optimizing-factual-correctness-summary-study/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhao Zhang, Derek Merck, Emily Tsai, et al.*2020 · 241 citations*
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