---
title: "Who cites Mustafa Suleyman — page 2 — 1,631 citing papers"
description: "1,631 papers of the Elamur Research library cite the works of Mustafa Suleyman, found in their bibliographies · page 2 of 4 · 101–200; the…"
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---
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# Who cites Mustafa Suleyman

1,631 citations of their works from 1,631 papers of our library (of the 149,439 whose bibliographies we read) · 321 with a page here, the most cited first · page 2 of 4 · 101–200 · [← Mustafa Suleyman](https://md.research.elamur.ai/free/en/authors/mustafa-suleyman/)

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101. **[Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/siriwardhana-2023-improving-domain-adaptation-retrieval-augmented/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, et al.*2023 · 403 citations*
102. **[TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance](https://md.research.elamur.ai/free/en/papers/zhu-2021-tat-qa-question-answering-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al.*2021 · 397 citations*
103. **[Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents](https://md.research.elamur.ai/free/en/papers/machado-2017-revisiting-arcade-learning-environment-evaluation/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, et al.*2017 · 393 citations*
104. **[Text Understanding with the Attention Sum Reader Network](https://md.research.elamur.ai/free/en/papers/kadlec-2016-text-understanding-attention-sum-reader/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rudolf Kadlec, Martin Schmid, Ondrej Bajgar, et al.*2016 · 390 citations*
105. [**Evaluation of Text Generation: A Survey arXiv:2006.14799**Asli Celikyilmaz, Elizabeth Clark, Jianfeng Gao*2020 · 388 citations*](https://md.research.elamur.ai/free/en/papers/celikyilmaz-2020-evaluation-text-generation-survey/)
106. [**ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension arXiv:1810.12885**Sheng Zhang, Xiaodong Liu, Jingjing Liu, et al.*2018 · 388 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-record-bridging-gap-between-human/)
107. [**CMMLU: Measuring massive multitask language understanding in Chinese arXiv:2306.09212**Haonan Li, Yixuan Zhang, Fajri Koto, et al.*2023 · 387 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cmmlu-measuring-massive-multitask-language/)
108. **[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*
109. **[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*
110. **[The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics](https://md.research.elamur.ai/free/en/papers/gehrmann-2021-gem-benchmark-natural-language-generation/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, et al.*2021 · 369 citations*
111. [**Identifying and Reducing Gender Bias in Word-Level Language Models arXiv:1904.03035**Shikha Bordia, Samuel R. Bowman*2019 · 367 citations*](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/)
112. [**How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks**Divyansh Kaushik, Zachary C. Lipton*2018 · 364 citations*](https://md.research.elamur.ai/free/en/papers/kaushik-2018-how-much-reading-does-reading/)
113. **[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*
114. **[Question Answering on Freebase via Relation Extraction and Textual Evidence](https://md.research.elamur.ai/free/en/papers/xu-2016-question-answering-freebase-relation-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kun Xu, Siva Reddy, Yansong Feng, et al.*2016 · 360 citations*
115. **[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*
116. **[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*
117. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 347 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/)
118. **[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*
119. **[DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-dream-challenge-data-set-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Jianshu Chen, et al.*2019 · 334 citations*
120. **[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*
121. **[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*
122. **[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*
123. **[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*
124. **[Multi-hop Reading Comprehension through Question Decomposition and Rescoring](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.*2019 · 312 citations*
125. **[UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 308 citations*
126. **[Muppet: Massive Multi-task Representations with Pre-Finetuning](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-muppet-massive-multi-task-representations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, et al.*2021 · 307 citations*
127. **[SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tu Vu, Brian Lester, Noah Constant, et al.*2022 · 306 citations*
128. **[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*
129. **[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*
130. **[Constructing Datasets for Multi-hop Reading Comprehension Across Documents](https://md.research.elamur.ai/free/en/papers/welbl-2018-constructing-datasets-multi-hop-reading/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Johannes Welbl, Pontus Stenetorp, Sebastian Riedel*2018 · 290 citations*
131. **[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*
132. **[emrQA: A Large Corpus for Question Answering on Electronic Medical Records](https://md.research.elamur.ai/free/en/papers/pampari-2018-emrqa-large-corpus-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anusri Pampari, Preethi Raghavan, Jennifer Liang, et al.*2018 · 289 citations*
133. [**Is ChatGPT a Good NLG Evaluator? A Preliminary Study arXiv:2303.04048**Jiaan Wang, Yunlong Liang, Fandong Meng, et al.*2023 · 287 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-chatgpt-good-nlg-evaluator-preliminary/)
134. **[TRUE: Re-evaluating Factual Consistency Evaluation](https://md.research.elamur.ai/free/en/papers/honovich-2022-true-re-evaluating-factual-consistency/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Or Honovich, Roee Aharoni, Jonathan Herzig, et al.*2022 · 279 citations*
135. **[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*
136. **[Reinforced Mnemonic Reader for Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/hu-2017-reinforced-mnemonic-reader-machine-reading/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Minghao Hu, Yuxing Peng, Zhen Huang, et al.*2017 · 273 citations*
137. **[Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge](https://md.research.elamur.ai/free/en/papers/mihaylov-2018-knowledgeable-reader-enhancing-cloze-style/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Todor Mihaylov, Anette Frank*2018 · 263 citations*
138. **[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*
139. **[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*
140. **[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*
141. **[Automatic Text Scoring Using Neural Networks](https://md.research.elamur.ai/free/en/papers/alikaniotis-2016-automatic-text-scoring-neural-networks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dimitrios Alikaniotis, Helen Yannakoudakis, Marek Rei*2016 · 259 citations*
142. **[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*
143. [**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/)
144. **[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*
145. **[NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark](https://md.research.elamur.ai/free/en/papers/sainz-2023-nlp-evaluation-trouble-need-measure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oscar Sainz, Jon Campos, Iker García-Ferrero, et al.*2023 · 250 citations*
146. **[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*
147. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
148. **[Dynamically Fused Graph Network for Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2019-dynamically-fused-graph-network-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lin Qiu, Yunxuan Xiao, Yanru Qu, et al.*2019 · 239 citations*
149. **[BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization](https://md.research.elamur.ai/free/en/papers/sharma-2019-bigpatent-large-scale-dataset-abstractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eva Sharma, Chen Li, Lu Wang*2019 · 236 citations*
150. **[MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension](https://md.research.elamur.ai/free/en/papers/talmor-2019-multiqa-empirical-investigation-generalization-transfer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alon Talmor, Jonathan Berant*2019 · 236 citations*
151. **[Compositional Questions Do Not Necessitate Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/min-2019-compositional-questions-do-not-necessitate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sewon Min, Eric Wallace, Sameer Singh, et al.*2019 · 235 citations*
152. **[Dialog State Tracking: A Neural Reading Comprehension Approach](https://md.research.elamur.ai/free/en/papers/gao-2019-dialog-state-tracking-neural-reading/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Shuyang Gao, Abhishek Sethi, Sanchit Agarwal, et al.*2019 · 234 citations*
153. **[Harvesting Paragraph-level Question-Answer Pairs from Wikipedia](https://md.research.elamur.ai/free/en/papers/du-2018-harvesting-paragraph-level-question-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinya Du, Claire Cardie*2018 · 232 citations*
154. [**A Diagram Is Worth A Dozen Images arXiv:1603.07396**Aniruddha Kembhavi, Mike Salvato, Eric Kolve, et al.*2016 · 231 citations*](https://md.research.elamur.ai/free/en/papers/kembhavi-2016-diagram-worth-dozen-images/)
155. **[Interpretation of Natural Language Rules in Conversational Machine Reading](https://md.research.elamur.ai/free/en/papers/saeidi-2018-interpretation-natural-language-rules-conversational/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Marzieh Saeidi, Max Bartolo, Patrick Lewis, et al.*2018 · 230 citations*
156. **[Commonsense for Generative Multi-Hop Question Answering Tasks](https://md.research.elamur.ai/free/en/papers/bauer-2018-commonsense-generative-multi-hop-question/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lisa Bauer, Yicheng Wang, Mohit Bansal*2018 · 229 citations*
157. **[Cross-topic Argument Mining from Heterogeneous Sources](https://md.research.elamur.ai/free/en/papers/stab-2018-cross-topic-argument-mining-heterogeneous/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christian Stab, Tristan Miller, Benjamin Schiller, et al.*2018 · 229 citations*
158. **[Searching for Effective Neural Extractive Summarization: What Works and What's Next](https://md.research.elamur.ai/free/en/papers/zhong-2019-searching-effective-neural-extractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhong, Pengfei Liu, Danqing Wang, et al.*2019 · 225 citations*
159. **[Annotating and Modeling Fine-grained Factuality in Summarization](https://md.research.elamur.ai/free/en/papers/goyal-2021-annotating-modeling-fine-grained-factuality/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tanya Goyal, Greg Durrett*2021 · 216 citations*
160. **[Answers Unite! Unsupervised Metrics for Reinforced Summarization Models](https://md.research.elamur.ai/free/en/papers/scialom-2019-answers-unite-unsupervised-metrics-reinforced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Scialom, Sylvain Lamprier, Benjamin Piwowarski, et al.*2019 · 214 citations*
161. **[Content Selection in Deep Learning Models of Summarization](https://md.research.elamur.ai/free/en/papers/kedzie-2018-content-selection-deep-learning-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chris Kedzie, Kathleen McKeown, Hal Daumé III*2018 · 214 citations*
162. **[Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts](https://md.research.elamur.ai/free/en/papers/clark-2019-sentence-mover-s-similarity-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elizabeth Clark, Asli Celikyilmaz, Noah A. Smith*2019 · 209 citations*
163. **[Towards a Unified Multi-Dimensional Evaluator for Text Generation](https://md.research.elamur.ai/free/en/papers/zhong-2022-unified-multi-dimensional-evaluator-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ming Zhong, Yang Liu, Da Yin, et al.*2022 · 208 citations*
164. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
165. **[TL;DR: Mining Reddit to Learn Automatic Summarization](https://md.research.elamur.ai/free/en/papers/volske-2017-tl-dr-mining-reddit-learn/) [Workshop on New Frontiers in Summarization](https://md.research.elamur.ai/free/en/venues/workshop-on-new-frontiers-in-summarization/)**Michael Völske, Martin Potthast, Shahbaz Syed, et al.*2017 · 204 citations*
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169. [**A Convolutional Attention Network for Extreme Summarization of Source Code arXiv:1602.03001**Miltiadis Allamanis, Hao Peng, Charles Sutton*2016 · 198 citations*](https://md.research.elamur.ai/free/en/papers/allamanis-2016-convolutional-attention-network-extreme-summarization/)
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177. **[What Makes Reading Comprehension Questions Easier?](https://md.research.elamur.ai/free/en/papers/sugawara-2018-what-makes-reading-comprehension-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Saku Sugawara, Kentaro Inui, Satoshi Sekine, et al.*2018 · 179 citations*
178. [**Improving Neural Language Models with a Continuous Cache arXiv:1612.04426**Edouard Grave, Armand Joulin, Nicolas Usunier*2016 · 179 citations*](https://md.research.elamur.ai/free/en/papers/grave-2016-improving-neural-language-models-continuous/)
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180. [**Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization arXiv:2210.01241**Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.*2022 · 174 citations*](https://md.research.elamur.ai/free/en/papers/ramamurthy-2022-reinforcement-learning-natural-language-processing/)
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183. [**DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications arXiv:1711.05073**Wei He, Kai Liu, Jing Liu, et al.*2017 · 170 citations*](https://md.research.elamur.ai/free/en/papers/he-2017-dureader-chinese-machine-reading/)
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187. **[Can We Automate Scientific Reviewing?](https://md.research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Weizhe Yuan, Pengfei Liu, Graham Neubig*2021 · 165 citations*
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189. **[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*
190. **[Question Answering for Privacy Policies: Combining Computational and Legal Perspectives](https://md.research.elamur.ai/free/en/papers/ravichander-2019-question-answering-privacy-policies-combining/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Abhilasha Ravichander, Alan W Black, Shomir Wilson, et al.*2019 · 163 citations*
191. [**A Span-Extraction Dataset for Chinese Machine Reading Comprehension arXiv:1810.07366 · EMNLP 2019 5886-5891**Yiming Cui, Ting Liu, Wanxiang Che, et al.*2018 · 160 citations*](https://md.research.elamur.ai/free/en/papers/cui-2018-span-extraction-dataset-chinese/)
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193. **[Scoring Sentence Singletons and Pairs for Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/lebanoff-2019-scoring-sentence-singletons-pairs-abstractive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Logan Lebanoff, Kaiqiang Song, Franck Dernoncourt, et al.*2019 · 159 citations*
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197. **[Exploring Versatile Generative Language Model Via Parameter-Efficient Transfer Learning](https://md.research.elamur.ai/free/en/papers/lin-2020-exploring-versatile-generative-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhaojiang Lin, Andrea Madotto, Pascale Fung*2020 · 152 citations*
198. **[HyperTree Proof Search for Neural Theorem Proving](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 151 citations*
199. **[Neural Models for Reasoning over Multiple Mentions Using Coreference](https://md.research.elamur.ai/free/en/papers/dhingra-2018-neural-models-reasoning-over-multiple/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bhuwan Dhingra, Qiao Jin, Zhilin Yang, et al.*2018 · 151 citations*
200. **[Discourse Parsing with Attention-based Hierarchical Neural Networks](https://md.research.elamur.ai/free/en/papers/li-2016-discourse-parsing-attention-based-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qi Li, Tianshi Li, Baobao Chang*2016 · 150 citations*

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