---
title: "Who cites Dropout: A Simple Way to — 2,041 citing papers"
description: "2,041 papers of the Elamur Research library cite «Dropout: A Simple Way to Prevent Neural Networks from Overfitting», found in their…"
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---
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# Who cites «Dropout: A Simple Way to Prevent Neural Networks from Overfitting»

2,041 papers of our library cite it (of the 149,439 whose bibliographies we read) · 242 with a page here, the most cited first · page 1 of 3 · 1–100 · [← back to «Dropout: A Simple Way to Prevent Neural Networks from Overfitting»](https://md.research.elamur.ai/free/en/papers/srivastava-2014-dropout-simple-way-prevent/)

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1. [**Attention Is All You Need arXiv:1706.03762**Ashish Vaswani, Noam Shazeer, Niki Parmar, et al.*2017 · 17,458 citations*](https://md.research.elamur.ai/free/en/papers/vaswani-2017-attention-all-need/)
2. [**Distilling the Knowledge in a Neural Network arXiv:1503.02531**Geoffrey Hinton, Oriol Vinyals, Jeff Dean*2015 · 15,229 citations*](https://md.research.elamur.ai/free/en/papers/hinton-2015-distilling-knowledge-neural-network/)
3. **[Deep Contextualized Word Representations](https://md.research.elamur.ai/free/en/papers/peters-2018-deep-contextualized-word-representations/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Matthew E. Peters, Mark Neumann, Mohit Iyyer, et al.*2018 · 14,944 citations*
4. [**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/)
5. [**YOLOv4: Optimal Speed and Accuracy of Object Detection arXiv:2004.10934**Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao*2020 · 10,403 citations*](https://md.research.elamur.ai/free/en/papers/bochkovskiy-2020-yolov4-optimal-speed-accuracy-object/)
6. [**Graph Attention Networks arXiv:1710.10903**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 9,035 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/)
7. [**Semi-Supervised Classification with Graph Convolutional Networks arXiv:1609.02907**Thomas N. Kipf, Max Welling*2016 · 9,023 citations*](https://md.research.elamur.ai/free/en/papers/kipf-2016-semi-supervised-classification-graph-convolutional/)
8. [**Explaining and Harnessing Adversarial Examples arXiv:1412.6572**Ian J. Goodfellow, Jonathon Shlens, Christian Szegedy*2014 · 8,577 citations*](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-explaining-harnessing-adversarial-examples/)
9. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention arXiv:1502.03044**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,670 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
10. **[Learning Transferable Architectures for Scalable Image Recognition](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.*2017 · 6,583 citations*
11. **[A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://md.research.elamur.ai/free/en/papers/williams-2018-broad-coverage-challenge-corpus-sentence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Adina Williams, Nikita Nangia, Samuel R. Bowman*2018 · 5,551 citations*
12. **[EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://md.research.elamur.ai/free/en/papers/tan-2019-efficientnet-rethinking-model-scaling-convolutional/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Mingxing Tan, Quoc V. Le*2019 · 5,416 citations*
13. **[A large annotated corpus for learning natural language inference](https://md.research.elamur.ai/free/en/papers/bowman-2015-large-annotated-corpus-learning-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Samuel R. Bowman, Gabor Angeli, Christopher Potts, et al.*2015 · 5,299 citations*
14. [**mixup: Beyond Empirical Risk Minimization arXiv:1710.09412**Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, et al.*2017 · 4,928 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-mixup-empirical-risk-minimization/)
15. **[SimCSE: Simple Contrastive Learning of Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/gao-2021-simcse-simple-contrastive-learning-sentence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyu Gao, Xingcheng Yao, Danqi Chen*2021 · 3,942 citations*
16. **[Conformer: Convolution-augmented Transformer for Speech Recognition](https://md.research.elamur.ai/free/en/papers/gulati-2020-conformer-convolution-augmented-transformer-speech/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Anmol Gulati, James Qin, Chung-Cheng Chiu, et al.*2020 · 3,475 citations*
17. [**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/)
18. **[Generating Sentences from a Continuous Space](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,435 citations*
19. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
20. **[Stacked Attention Networks for Image Question Answering](https://md.research.elamur.ai/free/en/papers/yang-2015-stacked-attention-networks-image-question/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Zichao Yang, Xiaodong He, Jianfeng Gao, et al.*2015 · 2,157 citations*
21. [**Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1 arXiv:1602.02830**Matthieu Courbariaux, Itay Hubara, Daniel Soudry, et al.*2016 · 2,143 citations*](https://md.research.elamur.ai/free/en/papers/courbariaux-2016-binarized-neural-networks-training-deep/)
22. [**Bidirectional Attention Flow for Machine Comprehension arXiv:1611.01603**Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, et al.*2016 · 1,988 citations*](https://md.research.elamur.ai/free/en/papers/seo-2016-bidirectional-attention-flow-machine-comprehension/)
23. [**BinaryConnect: Training Deep Neural Networks with binary weights during propagations arXiv:1511.00363**Matthieu Courbariaux, Yoshua Bengio, Jean-Pierre David*2015 · 1,885 citations*](https://md.research.elamur.ai/free/en/papers/courbariaux-2015-binaryconnect-training-deep-neural-networks/)
24. [**Quantized Neural Networks: Training Neural Networks with Low Precision Weights and Activations arXiv:1609.07061**Itay Hubara, Matthieu Courbariaux, Daniel Soudry, et al.*2016 · 1,610 citations*](https://md.research.elamur.ai/free/en/papers/hubara-2016-quantized-neural-networks-training-neural/)
25. **[End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Makoto Miwa, Mohit Bansal*2016 · 1,606 citations*
26. [**On the Convergence of Adam and Beyond arXiv:1904.09237**Sashank J. Reddi, Satyen Kale, Sanjiv Kumar*2019 · 1,598 citations*](https://md.research.elamur.ai/free/en/papers/reddi-2019-convergence-adam/)
27. **[Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates](https://md.research.elamur.ai/free/en/papers/kudo-2018-subword-regularization-improving-neural-network/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taku Kudo*2018 · 1,573 citations*
28. [**Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models arXiv:1411.2539**Ryan Kiros, Ruslan Salakhutdinov, Richard S. Zemel*2014 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/kiros-2014-unifying-visual-semantic-embeddings-multimodal/)
29. [**Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning arXiv:1709.00103**Victor Zhong, Caiming Xiong, Richard Socher*2017 · 1,226 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2017-seq2sql-generating-structured-queries-natural/)
30. **[Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems](https://md.research.elamur.ai/free/en/papers/wen-2015-semantically-conditioned-lstm-based-natural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, et al.*2015 · 1,202 citations*
31. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
32. [**A Theoretically Grounded Application of Dropout in Recurrent Neural Networks arXiv:1512.05287**Yarin Gal, Zoubin Ghahramani*2015 · 1,032 citations*](https://md.research.elamur.ai/free/en/papers/gal-2015-theoretically-grounded-application-dropout-recurrent/)
33. **[Chinese NER Using Lattice LSTM](https://md.research.elamur.ai/free/en/papers/zhang-2018-chinese-ner-lattice-lstm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Zhang, Jie Yang*2018 · 998 citations*
34. [**Segment Anything arXiv:2304.02643**Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.*2023 · 960 citations*](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/)
35. **[Deep Unordered Composition Rivals Syntactic Methods for Text Classification](https://md.research.elamur.ai/free/en/papers/iyyer-2015-deep-unordered-composition-rivals-syntactic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, et al.*2015 · 926 citations*
36. [**End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF arXiv:1603.01354**Xuezhe Ma, Eduard Hovy*2016 · 868 citations*](https://md.research.elamur.ai/free/en/papers/ma-2016-end-end-sequence-labeling-bi/)
37. **[DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding](https://md.research.elamur.ai/free/en/papers/shen-2017-disan-directional-self-attention-network/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Tao Shen, Tianyi Zhou, Guodong Long, et al.*2017 · 854 citations*
38. **[Gated Self-Matching Networks for Reading Comprehension and Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2017-gated-self-matching-networks-reading/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhui Wang, Nan Yang, Furu Wei, et al.*2017 · 833 citations*
39. **[ERASER: A Benchmark to Evaluate Rationalized NLP Models](https://md.research.elamur.ai/free/en/papers/deyoung-2020-eraser-benchmark-evaluate-rationalized-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, et al.*2020 · 832 citations*
40. **[Scaling Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 826 citations*
41. [**TuckER: Tensor Factorization for Knowledge Graph Completion arXiv:1901.09590**Ivana Balažević, Carl Allen, Timothy M. Hospedales*2019 · 799 citations*](https://md.research.elamur.ai/free/en/papers/balazevic-2019-tucker-tensor-factorization-knowledge-graph/)
42. **[SoundStream: An End-to-End Neural Audio Codec](https://md.research.elamur.ai/free/en/papers/zeghidour-2021-soundstream-end-end-neural-audio/) [IEEE/ACM Transactions on Audio Speech and Language Processing](https://md.research.elamur.ai/free/en/venues/ieee-acm-transactions-on-audio-speech-and-language-processing/)**Neil Zeghidour, Alejandro Luebs, Ahmed Omran, et al.*2021 · 733 citations*
43. **[Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation](https://md.research.elamur.ai/free/en/papers/chen-2019-progressive-differentiable-architecture-search-bridging/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Xin Chen, Lingxi Xie, Jun Wu, et al.*2019 · 732 citations*
44. [**The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks arXiv:1802.08232**Nicholas Carlini, Chang Liu, Ulfar Erlingsson, et al.*2018 · 692 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2018-secret-sharer-evaluating-testing-unintended/)
45. **[A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 674 citations*
46. [**PathNet: Evolution Channels Gradient Descent in Super Neural Networks arXiv:1701.08734**Chrisantha Fernando, Dylan Banarse, Charles Blundell, et al.*2017 · 667 citations*](https://md.research.elamur.ai/free/en/papers/fernando-2017-pathnet-evolution-channels-gradient-descent/)
47. [**How Powerful are Graph Neural Networks? arXiv:1810.00826**Keyulu Xu, Weihua Hu, Jure Leskovec, et al.*2018 · 655 citations*](https://md.research.elamur.ai/free/en/papers/xu-2018-powerful-graph-neural-networks/)
48. **[A Neural Approach to Automated Essay Scoring](https://md.research.elamur.ai/free/en/papers/taghipour-2016-neural-approach-automated-essay-scoring/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaveh Taghipour, Hwee Tou Ng*2016 · 654 citations*
49. **[Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging](https://md.research.elamur.ai/free/en/papers/reimers-2017-reporting-score-distributions-makes-difference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nils Reimers, Iryna Gurevych*2017 · 652 citations*
50. [**Regularizing and Optimizing LSTM Language Models arXiv:1708.02182**Stephen Merity, Nitish Shirish Keskar, Richard Socher*2017 · 633 citations*](https://md.research.elamur.ai/free/en/papers/merity-2017-regularizing-optimizing-lstm-language-models/)
51. **[Efficient Intent Detection with Dual Sentence Encoders](https://md.research.elamur.ai/free/en/papers/casanueva-2020-efficient-intent-detection-dual-sentence/) [Workshop on Natural Language Processing for Conversational AI](https://md.research.elamur.ai/free/en/venues/nlp4convai/)**Iñigo Casanueva, Tadas Temčinas, Daniela Gerz, et al.*2020 · 628 citations*
52. **[Linguistically-Informed Self-Attention for Semantic Role Labeling](https://md.research.elamur.ai/free/en/papers/strubell-2018-linguistically-informed-self-attention-semantic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emma Strubell, Patrick Verga, Daniel Andor, et al.*2018 · 604 citations*
53. [**Dynamic Coattention Networks For Question Answering arXiv:1611.01604**Caiming Xiong, Victor Zhong, Richard Socher*2016 · 596 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2016-dynamic-coattention-networks-question-answering/)
54. **[DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/baziotis-2017-datastories-semeval-2017-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Christos Baziotis, Nikos Pelekis, Christos Doulkeridis*2017 · 588 citations*
55. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges arXiv:1907.05019**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 564 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
56. [**Reducing Transformer Depth on Demand with Structured Dropout arXiv:1909.11556**Angela Fan, Edouard Grave, Armand Joulin*2019 · 560 citations*](https://md.research.elamur.ai/free/en/papers/fan-2019-reducing-transformer-depth-demand-structured/)
57. [**SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine arXiv:1704.05179**Matthew Dunn, Levent Sagun, Mike Higgins, et al.*2017 · 555 citations*](https://md.research.elamur.ai/free/en/papers/dunn-2017-searchqa-new-q-dataset-augmented/)
58. **[Fast and Accurate Entity Recognition with Iterated Dilated Convolutions](https://md.research.elamur.ai/free/en/papers/strubell-2017-fast-accurate-entity-recognition-iterated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emma Strubell, Patrick Verga, David Belanger, et al.*2017 · 548 citations*
59. **[Simple, Scalable Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bapna-2019-simple-scalable-adaptation-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ankur Bapna, Orhan Firat*2019 · 530 citations*
60. **[ICON: Interactive Conversational Memory Network for Multimodal Emotion Detection](https://md.research.elamur.ai/free/en/papers/hazarika-2018-icon-interactive-conversational-memory-network/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Devamanyu Hazarika, Soujanya Poria, Rada Mihalcea, et al.*2018 · 526 citations*
61. [**Regularizing Neural Networks by Penalizing Confident Output Distributions arXiv:1701.06548**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 496 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
62. **[A Convolutional Encoder Model for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-encoder-model-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jonas Gehring, Michael Auli, David Grangier, et al.*2017 · 492 citations*
63. [**Deep Exploration via Bootstrapped DQN arXiv:1602.04621**Ian Osband, Charles Blundell, Alexander Pritzel, et al.*2016 · 490 citations*](https://md.research.elamur.ai/free/en/papers/osband-2016-deep-exploration-bootstrapped-dqn/)
64. **[Legal Judgment Prediction via Topological Learning](https://md.research.elamur.ai/free/en/papers/zhong-2018-legal-judgment-prediction-topological-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoxi Zhong, Zhipeng Guo, Cunchao Tu, et al.*2018 · 480 citations*
65. **[Joint Embedding of Words and Labels for Text Classification](https://md.research.elamur.ai/free/en/papers/wang-2018-joint-embedding-words-labels-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guoyin Wang, Chunyuan Li, Wenlin Wang, et al.*2018 · 465 citations*
66. [**CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning arXiv:1612.06890**Justin Johnson, Bharath Hariharan, Laurens van der Maaten, et al.*2016 · 464 citations*](https://md.research.elamur.ai/free/en/papers/johnson-2016-clevr-diagnostic-dataset-compositional-language/)
67. **[Graph-to-Sequence Learning using Gated Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/beck-2018-graph-sequence-learning-gated-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daniel Beck, Gholamreza Haffari, Trevor Cohn*2018 · 459 citations*
68. [**FreeLB: Enhanced Adversarial Training for Natural Language Understanding arXiv:1909.11764**Chen Zhu, Yu Cheng, Zhe Gan, et al.*2019 · 452 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/)
69. **[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*
70. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
71. [**Adversarial Training Methods for Semi-Supervised Text Classification arXiv:1605.07725**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 433 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/)
72. **[Depression and Self-Harm Risk Assessment in Online Forums](https://md.research.elamur.ai/free/en/papers/yates-2017-depression-self-harm-risk-assessment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andrew Yates, Arman Cohan, Nazli Goharian*2017 · 404 citations*
73. **[BPE-Dropout: Simple and Effective Subword Regularization](https://md.research.elamur.ai/free/en/papers/provilkov-2020-bpe-dropout-simple-effective-subword/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ivan Provilkov, Dmitrii Emelianenko, Elena Voita*2020 · 391 citations*
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