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title: "Who cites Abstractive Text — page 2 — 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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# 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 2 of 2 · 101–142 · [← 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/)

[← prev](https://md.research.elamur.ai/free/en/papers/nallapati-2016-abstractive-text-summarization-sequence-sequence/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/nallapati-2016-abstractive-text-summarization-sequence-sequence/cited-by/) **2**

101. **[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*
102. **[LongEval: Guidelines for Human Evaluation of Faithfulness in Long-form Summarization](https://md.research.elamur.ai/free/en/papers/krishna-2023-longeval-guidelines-human-evaluation-faithfulness/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kalpesh Krishna, Erin Bransom, Bailey Kuehl, et al.*2023 · 114 citations*
103. **[Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation](https://md.research.elamur.ai/free/en/papers/deng-2021-compression-transduction-creation-unified-framework/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingkai Deng, Bowen Tan, Zhengzhong Liu, et al.*2021 · 102 citations*
104. **[On Learning to Summarize with Large Language Models as References](https://md.research.elamur.ai/free/en/papers/liu-2024-learning-summarize-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yixin Liu, Kejian Shi, Katherine He, et al.*2024 · 94 citations*
105. [**Large Language Models are Inconsistent and Biased Evaluators arXiv:2405.01724**Rickard Stureborg, Dimitris Alikaniotis, Yoshi Suhara*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/stureborg-2024-large-language-models-inconsistent-biased/)
106. **[Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence Tasks](https://md.research.elamur.ai/free/en/papers/sottana-2023-evaluation-metrics-era-gpt-4/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andrea Sottana, Bin Liang, Kai Zou, et al.*2023 · 89 citations*
107. **[FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-followbench-multi-level-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.*2024 · 86 citations*
108. [**Pragmatically Informative Text Generation**Sheng Shen, Daniel Fried, Jacob Andreas, et al.*2019 · 78 citations*](https://md.research.elamur.ai/free/en/papers/shen-2019-pragmatically-informative-text-generation/)
109. **[Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/laskar-2022-domain-adaptation-pre-trained-transformers/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang*2022 · 76 citations*
110. **[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*
111. **[Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback](https://md.research.elamur.ai/free/en/papers/roit-2023-factually-consistent-summarization-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Roit, Johan Ferret, Lior Shani, et al.*2023 · 70 citations*
112. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
113. **[Bias in Large Language Models: Origin, Evaluation, and Mitigation](https://md.research.elamur.ai/free/en/papers/guo-2024-bias-large-language-models-origin/) [Electronics](https://md.research.elamur.ai/free/en/venues/electronics/)**Yufei Guo, Muzhe Guo, Juntao Su, et al.*2024 · 58 citations*
114. **[A Systematic Survey of Automatic Prompt Optimization Techniques](https://md.research.elamur.ai/free/en/papers/ramnath-2025-systematic-survey-automatic-prompt-optimization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kiran Ramnath, Kang Zhou, Sheng Guan, et al.*2025 · 40 citations*
115. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
116. [**Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing arXiv:2305.16635**Jaehun Jung, Peter West, Liwei Jiang, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/jung-2023-impossible-distillation-low-quality-model/)
117. **[MEGA RST Discourse Treebanks with Structure and Nuclearity from Scalable Distant Sentiment Supervision](https://md.research.elamur.ai/free/en/papers/huber-2020-mega-rst-discourse-treebanks-structure/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Patrick Huber, Giuseppe Carenini*2020 · 35 citations*
118. **[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*
119. **[Detection and Measurement of Syntactic Templates in Generated Text](https://md.research.elamur.ai/free/en/papers/shaib-2024-detection-measurement-syntactic-templates-generated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chantal Shaib, Yanai Elazar, Junyi Jessy Li, et al.*2024 · 32 citations*
120. **[Pairwise Representation Learning for Event Coreference](https://md.research.elamur.ai/free/en/papers/yu-2022-pairwise-representation-learning-event-coreference/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Xiaodong Yu, Wenpeng Yin, Dan Roth*2022 · 31 citations*
121. **[Evaluating Document Coherence Modeling](https://md.research.elamur.ai/free/en/papers/shen-2021-evaluating-document-coherence-modeling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aili Shen, Meladel Mistica, Bahar Salehi, et al.*2021 · 30 citations*
122. **[Investigating Hallucinations in Pruned Large Language Models for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/chrysostomou-2024-investigating-hallucinations-pruned-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**George Chrysostomou, Zhixue Zhao, Miles Williams, et al.*2024 · 27 citations*
123. [**Language Model Self-improvement by Reinforcement Learning Contemplation arXiv:2305.14483**Jing-Cheng Pang; Pengyuan Wang; Kaiyuan Li; Xiong-Hui Chen; Jiacheng Xu; Zongzhang Zhang;, Yang Yu*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/pang-2023-language-model-self-improvement-reinforcement/)
124. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
125. **[Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text Generation](https://md.research.elamur.ai/free/en/papers/zhou-2025-balancing-diversity-risk-llm-sampling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxuan Zhou, Margret Keuper, Mario Fritz*2025 · 11 citations*
126. [**HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew**Tzuf Paz-Argaman, Itai Mondshine, Asaf Achi Mordechai, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/argaman-2024-hesum-novel-dataset-abstractive-text/)
127. [**Amharic Abstractive Text Summarization arXiv:2003.13721**Amr M. Zaki, Mahmoud I. Khalil, Hazem M. Abbas*2020 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zaki-2020-amharic-abstractive-text-summarization/)
128. **[LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation](https://md.research.elamur.ai/free/en/papers/liu-2026-logitspec-accelerating-retrieval-based-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Liu, Qitan Lv, Hao Li, et al.*2026 · 6 citations*
129. **[KNN-SSD: Enabling Dynamic Self-Speculative Decoding via Nearest Neighbor Layer Set Optimization](https://md.research.elamur.ai/free/en/papers/song-2026-knn-ssd-enabling-dynamic-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingbo Song, Heming Xia, Jun Zhang, et al.*2026 · 5 citations*
130. **[WikiVideo: Article Generation from Multiple Videos](https://md.research.elamur.ai/free/en/papers/martin-2026-wikivideo-article-generation-multiple-videos/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alexander Martin, Reno Kriz, William Gantt Walden, et al.*2026 · 5 citations*
131. [**LSTM-Based Text Generation: A Study on Historical Datasets arXiv:2403.07087 · 16th International Istanbul Scientific Research Congress on Life, Engineering, Architecture, and Mathematical Sciences Proceedings Book, Pages: 42-49, 2024**Mustafa Abbas Hussein Hussein, Serkan Savaş*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hussein-2024-lstm-based-text-generation-study/)
132. **[Sparse Brains are Also Adaptive Brains: Cognitive-Load-Aware Dynamic Activation for LLMs](https://md.research.elamur.ai/free/en/papers/yang-2026-sparse-brains-are-also-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiheng Yang, Yujie Wang, Chi Ma, et al.*2026 · 3 citations*
133. **[Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation](https://md.research.elamur.ai/free/en/papers/he-2018-exploring-textual-speech-information-dialogue/) [Annual Workshop of the Australasian Language Technology Association (ALTA)](https://md.research.elamur.ai/free/en/venues/alta/)**Xuanli He, Quan Tran, William Havard, et al.*2018 · 3 citations*
134. **[Attribution, Citation, and Quotation: A Survey of Evidence-based Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/schreieder-2026-attribution-citation-quotation-survey-evidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tobias Schreieder, Tim Schopf, Michael Färber*2026 · 1 citation*
135. **[FaithLens: Detecting and Explaining Faithfulness Hallucination](https://md.research.elamur.ai/free/en/papers/si-2026-faithlens-detecting-explaining-faithfulness-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuzheng Si, Qingyi Wang, Haozhe Zhao, et al.*2026 · 1 citation*
136. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
137. **[Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks](https://md.research.elamur.ai/free/en/papers/pankratov-2026-speculative-decoding-speed-light-optimal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sergey Pankratov, Dan Alistarh*2026 · 1 citation*
138. **[AnalystBench: Benchmarking professional long-form report generation with web-mined multimodal tasks](https://md.research.elamur.ai/free/en/papers/pham-2026-analystbench-benchmarking-professional-long-form/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chau Minh Pham, Zichao Wang, Puneet Mathur, et al.*2026*
139. **[Learning to Control Summaries with Score Ranking](https://md.research.elamur.ai/free/en/papers/liu-2026-learning-control-summaries-score-ranking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongye Liu, Liang Ding, Ricardo Henao*2026*
140. **[SCURank: Ranking Multiple Candidate Summaries with Summary Content Units for Enhanced Summarization](https://md.research.elamur.ai/free/en/papers/wang-2026-scurank-ranking-multiple-candidate-summaries/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo-Jyun Wang, Ying-Jia Lin, Hung-Yu Kao*2026*
141. **[Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-Tuning](https://md.research.elamur.ai/free/en/papers/schaffelder-2026-synthetic-eggs-many-baskets-impact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Max Schaffelder, Albert Gatt*2026*
142. [**Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language**Vitaly Shalumov, Harel Haskey, Yuval Solaz*2024*](https://md.research.elamur.ai/free/en/papers/shalumov-2024-mevaker-conclusion-extraction-allocation-resources/)

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