---
title: "Who cites David Warde-Farley — 1,462 papers of our library"
description: "1,462 papers of the Elamur Research library cite the works of David Warde-Farley, found in their bibliographies · page 1 of 2 · 1–100; the…"
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---
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# Who cites David Warde-Farley

1,467 citations of their works from 1,462 papers of our library (of the 149,439 whose bibliographies we read) · 128 with a page here, the most cited first · page 1 of 2 · 1–100 · [← David Warde-Farley](https://md.research.elamur.ai/free/en/authors/david-warde-farley/)

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1. **[Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/cho-2014-learning-phrase-representations-rnn-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kyunghyun Cho, Bart van Merriënboer, Caglar Gulcehre, et al.*2014 · 26,725 citations*
2. [**Neural Machine Translation by Jointly Learning to Align and Translate arXiv:1409.0473**Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio*2014 · 19,287 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2014-neural-machine-translation-jointly-learning/)
3. **[Momentum Contrast for Unsupervised Visual Representation Learning](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) [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/)**Kaiming He, Haoqi Fan, Yuxin Wu, et al.*2019 · 13,302 citations*
4. **[A Comprehensive Survey on Graph Neural Networks](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/) [IEEE Transactions on Neural Networks and Learning Systems](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-neural-networks-and-learning-systems/)**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,312 citations*
5. [**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/)
6. [**A Simple Framework for Contrastive Learning of Visual Representations arXiv:2002.05709**Ting Chen, Simon Kornblith, Mohammad Norouzi, et al.*2020 · 8,000 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-simple-framework-contrastive-learning-visual/)
7. [**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/)
8. [**Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks arXiv:1511.06434**Alec Radford, Luke Metz, Soumith Chintala*2015 · 6,654 citations*](https://md.research.elamur.ai/free/en/papers/radford-2015-unsupervised-representation-learning-deep-convolutional/)
9. [**Generative Adversarial Nets**Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, et al.*2014 · 5,790 citations*](https://md.research.elamur.ai/free/en/papers/goodfellow-2014-generative-adversarial-nets/)
10. [**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/)
11. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
12. [**Hierarchical Text-Conditional Image Generation with CLIP Latents arXiv:2204.06125**Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, et al.*2022 · 2,713 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2022-hierarchical-text-conditional-image-generation/)
13. **[Scalable Diffusion Models with Transformers](https://md.research.elamur.ai/free/en/papers/peebles-2022-scalable-diffusion-models-transformers/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**William Peebles, Saining Xie*2022 · 2,670 citations*
14. **[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*
15. [**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/)
16. [**MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems arXiv:1512.01274**Tianqi Chen, Mu Li, Yutian Li, et al.*2015 · 2,000 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-mxnet-flexible-efficient-machine-learning/)
17. [**Adversarial Examples for Evaluating Reading Comprehension Systems**Robin Jia, Percy Liang*2017 · 1,969 citations*](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/)
18. [**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/)
19. [**Attention-Based Models for Speech Recognition arXiv:1506.07503**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
20. [**Deep Unsupervised Learning using Nonequilibrium Thermodynamics arXiv:1503.03585**Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, et al.*2015 · 1,761 citations*](https://md.research.elamur.ai/free/en/papers/sohl-dickstein-2015-deep-unsupervised-learning-using-nonequilibrium/)
21. [**Score-Based Generative Modeling through Stochastic Differential Equations arXiv:2011.13456**Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, et al.*2020 · 1,680 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-score-based-generative-modeling-through/)
22. [**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/)
23. [**Improved Techniques for Training GANs arXiv:1606.03498**Tim Salimans, Ian Goodfellow, Wojciech Zaremba, et al.*2016 · 1,558 citations*](https://md.research.elamur.ai/free/en/papers/salimans-2016-improved-techniques-training-gans/)
24. [**Zero-Shot Text-to-Image Generation arXiv:2102.12092**Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, et al.*2021 · 1,528 citations*](https://md.research.elamur.ai/free/en/papers/ramesh-2021-zero-shot-text-image-generation/)
25. **[Pre-Training with Whole Word Masking for Chinese BERT](https://md.research.elamur.ai/free/en/papers/cui-2019-pre-training-whole-word-masking/) [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/)**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2019 · 1,490 citations*
26. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning arXiv:1802.04799**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,384 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
27. [**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/)
28. [**Generative Modeling by Estimating Gradients of the Data Distribution arXiv:1907.05600**Yang Song, Stefano Ermon*2019 · 1,274 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/)
29. **[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*
30. **[On Using Very Large Target Vocabulary for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/jean-2015-very-large-target-vocabulary-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sébastien Jean, Kyunghyun Cho, Roland Memisevic, et al.*2015 · 1,013 citations*
31. [**Convolutional Networks on Graphs for Learning Molecular Fingerprints arXiv:1509.09292**David Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, et al.*2015 · 993 citations*](https://md.research.elamur.ai/free/en/papers/duvenaud-2015-convolutional-networks-graphs-learning-molecular/)
32. [**Style Transfer from Non-Parallel Text by Cross-Alignment**Tianxiao Shen, Tao Lei, Regina Barzilay, et al.*2017 · 979 citations*](https://md.research.elamur.ai/free/en/papers/shen-2017-style-transfer-non-parallel-text/)
33. [**Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges arXiv:2103.11251 · Statistics Surveys, 2021**Cynthia Rudin; Chaofan Chen; Zhi Chen; Haiyang Huang; Lesia Semenova;, Chudi Zhong*2021 · 974 citations*](https://md.research.elamur.ai/free/en/papers/rudin-2021-interpretable-machine-learning-fundamental/)
34. [**HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis arXiv:2010.05646**Jungil Kong, Jaehyeon Kim, Jaekyoung Bae*2020 · 969 citations*](https://md.research.elamur.ai/free/en/papers/kong-2020-hifi-gan-generative-adversarial-networks/)
35. **[Multi-Task Learning for Multiple Language Translation](https://md.research.elamur.ai/free/en/papers/dong-2015-multi-task-learning-multiple-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Daxiang Dong, Hua Wu, Wei He, et al.*2015 · 796 citations*
36. [**Revisiting Pre-Trained Models for Chinese Natural Language Processing arXiv:2004.13922**Yiming Cui, Wanxiang Che, Ting Liu, et al.*2020 · 790 citations*](https://md.research.elamur.ai/free/en/papers/cui-2020-revisiting-pre-trained-models-chinese/)
37. **[Analysis Methods in Neural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yonatan Belinkov, James Glass*2019 · 740 citations*
38. **[Mitigating Gender Bias in Natural Language Processing: Literature Review](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tony Sun, Andrew Gaut, Shirlyn Tang, et al.*2019 · 724 citations*
39. **[Style Transfer in Text: Exploration and Evaluation](https://md.research.elamur.ai/free/en/papers/fu-2017-style-transfer-text-exploration-evaluation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Zhenxin Fu, Xiaoye Tan, Nanyun Peng, et al.*2017 · 703 citations*
40. **[Red Teaming Language Models with Language Models](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 700 citations*
41. [**Unsupervised Machine Translation Using Monolingual Corpora Only arXiv:1711.00043**Guillaume Lample, Alexis Conneau, Ludovic Denoyer, et al.*2017 · 669 citations*](https://md.research.elamur.ai/free/en/papers/lample-2017-unsupervised-machine-translation-using-monolingual/)
42. [**Denoising Diffusion Implicit Models arXiv:2010.02502**Jiaming Song, Chenlin Meng, Stefano Ermon*2020 · 576 citations*](https://md.research.elamur.ai/free/en/papers/song-2020-denoising-diffusion-implicit-models/)
43. **[Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models](https://md.research.elamur.ai/free/en/papers/serban-2015-building-end-end-dialogue-systems/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio, et al.*2015 · 551 citations*
44. [**Toward Controlled Generation of Text arXiv:1703.00955**Zhiting Hu, Zichao Yang, Xiaodan Liang, et al.*2017 · 537 citations*](https://md.research.elamur.ai/free/en/papers/hu-2017-toward-controlled-generation-text/)
45. [**Texygen: A Benchmarking Platform for Text Generation Models arXiv:1802.01886**Yaoming Zhu, Sidi Lu, Lei Zheng, et al.*2018 · 495 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2018-texygen-benchmarking-platform-text-generation/)
46. **[Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection](https://md.research.elamur.ai/free/en/papers/ravfogel-2020-null-it-out-guarding-protected/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shauli Ravfogel, Yanai Elazar, Hila Gonen, et al.*2020 · 488 citations*
47. [**CogView: Mastering Text-to-Image Generation via Transformers arXiv:2105.13290**Ming Ding, Zhuoyi Yang, Wenyi Hong, et al.*2021 · 469 citations*](https://md.research.elamur.ai/free/en/papers/ding-2021-cogview-mastering-text-image/)
48. **[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*
49. **[A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://md.research.elamur.ai/free/en/papers/hedderich-2021-survey-recent-approaches-natural-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Michael A. Hedderich, Lukas Lange, Heike Adel, et al.*2021 · 401 citations*
50. **[On the Limitations of Unsupervised Bilingual Dictionary Induction](https://md.research.elamur.ai/free/en/papers/sogaard-2018-limitations-unsupervised-bilingual-dictionary-induction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anders Søgaard, Sebastian Ruder, Ivan Vulić*2018 · 401 citations*
51. **[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*
52. [**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/)
53. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
54. **[Adversarial Training for Unsupervised Bilingual Lexicon Induction](https://md.research.elamur.ai/free/en/papers/zhang-2017-adversarial-training-unsupervised-bilingual-lexicon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meng Zhang, Yang Liu, Huanbo Luan, et al.*2017 · 362 citations*
55. **[Adversarial Removal of Demographic Attributes from Text Data](https://md.research.elamur.ai/free/en/papers/elazar-2018-adversarial-removal-demographic-attributes-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanai Elazar, Yoav Goldberg*2018 · 359 citations*
56. **[Neural Unsupervised Domain Adaptation in NLP–-A Survey](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Alan Ramponi, Barbara Plank*2020 · 336 citations*
57. [**Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow arXiv:2209.03003**Xingchao Liu, Chengyue Gong, Qiang Liu*2022 · 315 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/)
58. **[A Survey of Domain Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenhui Chu, Rui Wang*2018 · 308 citations*
59. **[Learning to Write with Cooperative Discriminators](https://md.research.elamur.ai/free/en/papers/holtzman-2018-learning-write-cooperative-discriminators/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ari Holtzman, Jan Buys, Maxwell Forbes, et al.*2018 · 303 citations*
60. [**How to Construct Deep Recurrent Neural Networks arXiv:1312.6026**Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, et al.*2013 · 302 citations*](https://md.research.elamur.ai/free/en/papers/pascanu-2013-construct-deep-recurrent-neural-networks/)
61. **[Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation](https://md.research.elamur.ai/free/en/papers/dai-2019-style-transformer-unpaired-text-style/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Dai, Jianze Liang, Xipeng Qiu, et al.*2019 · 301 citations*
62. **[Paraphrase Generation with Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/li-2018-paraphrase-generation-deep-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichao Li, Xin Jiang, Lifeng Shang, et al.*2018 · 300 citations*
63. **[Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack](https://md.research.elamur.ai/free/en/papers/dinan-2019-build-it-break-it-fix/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emily Dinan, Samuel Humeau, Bharath Chintagunta, et al.*2019 · 295 citations*
64. [**Structured Denoising Diffusion Models in Discrete State-Spaces arXiv:2107.03006**Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al.*2021 · 284 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-structured-denoising-diffusion-models-discrete/)
65. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
66. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)
67. **[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*
68. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 254 citations*
69. [**Generative Language Modeling for Automated Theorem Proving arXiv:2009.03393**Stanislas Polu, Ilya Sutskever*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/polu-2020-generative-language-modeling-automated-theorem/)
70. **[Towards Robust Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/cheng-2018-robust-neural-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yong Cheng, Zhaopeng Tu, Fandong Meng, et al.*2018 · 238 citations*
71. [**Concrete Problems in AI Safety arXiv:1606.06565**Dario Amodei, Chris Olah, Jacob Steinhardt, et al.*2016 · 232 citations*](https://md.research.elamur.ai/free/en/papers/amodei-2016-concrete-problems-ai-safety/)
72. **[Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking](https://md.research.elamur.ai/free/en/papers/wen-2015-stochastic-language-generation-dialogue-recurrent/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Tsung-Hsien Wen, Milica Gašić, Dongho Kim, et al.*2015 · 216 citations*
73. **[Data-Driven Sentence Simplification: Survey and Benchmark](https://md.research.elamur.ai/free/en/papers/manchego-2020-data-driven-sentence-simplification-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Fernando Alva-Manchego, Carolina Scarton, Lucia Specia*2020 · 213 citations*
74. **[Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer](https://md.research.elamur.ai/free/en/papers/santos-2018-fighting-offensive-language-social-media/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cicero Nogueira dos Santos, Igor Melnyk, Inkit Padhi*2018 · 211 citations*
75. [**CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers arXiv:2205.15868**Wenyi Hong, Ming Ding, Wendi Zheng, et al.*2022 · 191 citations*](https://md.research.elamur.ai/free/en/papers/hong-2022-cogvideo-large-scale-pretraining/)
76. [**DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models arXiv:2210.08933**Shansan Gong, Mukai Li, Jiangtao Feng, et al.*2022 · 189 citations*](https://md.research.elamur.ai/free/en/papers/gong-2022-diffuseq-sequence-sequence-text-generation/)
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89. [**Unifying Human and Statistical Evaluation for Natural Language Generation arXiv:1904.02792**Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang*2019 · 143 citations*](https://md.research.elamur.ai/free/en/papers/hashimoto-2019-unifying-human-statistical-evaluation-natural/)
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