---
title: "Kyunghyun Cho — all works — Elamur Research"
description: "All 483 works of Kyunghyun Cho in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
canonical: "https://research.elamur.ai/free/en/authors/kyunghyun-cho/works/"
---
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# Kyunghyun Cho — all works

483 works · page 1 of 5 · 1–100 · [← Kyunghyun Cho](https://md.research.elamur.ai/free/en/authors/kyunghyun-cho/)

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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. **[Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling ↗](https://arxiv.org/abs/1412.3555) arXiv:1412.3555 · no summary yet**Junyoung Chung et al.*2014 · 10,908 citations*
4. [**On the Properties of Neural Machine Translation: Encoder-Decoder Approaches arXiv:1409.1259**Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, et al.*2014 · 7,803 citations*](https://md.research.elamur.ai/free/en/papers/cho-2014-properties-neural-machine-translation-encoder/)
5. [**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/)
6. **[Recurrent Neural Networks for Multivariate Time Series with Missing Values ↗](https://doi.org/10.1038/s41598-018-24271-9) Scientific Reports · no summary yet**Zhengping Che et al.*2016 · 2,332 citations*
7. [**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/)
8. **[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*
9. [**AdapterFusion: Non-Destructive Task Composition for Transfer Learning arXiv:2005.00247 · Proceedings of EACL 2021**Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, et al.*2020 · 958 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterfusion-non-destructive-task-composition/)
10. **[Structure-based protein function prediction using graph convolutional networks ↗](https://doi.org/10.1038/s41467-021-23303-9) Nature Communications · no summary yet**Vladimir Gligorijević et al.*2021 · 918 citations*
11. **[Joint Event Extraction via Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/nguyen-2016-joint-event-extraction-recurrent-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Thien Huu Nguyen, Kyunghyun Cho, Ralph Grishman*2016 · 882 citations*
12. **[Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Orhan Firat, Kyunghyun Cho, Yoshua Bengio*2016 · 833 citations*
13. **[Identifying and attacking the saddle point problem in high-dimensional non-convex optimization ↗](https://arxiv.org/abs/1406.2572) arXiv (Cornell University) · no summary yet**Yann Dauphin et al.*2014 · 818 citations*
14. **[On the Number of Linear Regions of Deep Neural Networks ↗](https://arxiv.org/abs/1402.1869) arXiv (Cornell University) · no summary yet**Guido Montúfar et al.*2014 · 811 citations*
15. **[Augmentation for small object detection ↗](https://doi.org/10.5121/csit.2019.91713) arXiv:1902.07296 · no summary yet**Máté Kisantal et al.*2019 · 796 citations*
16. **[Learning Distributed Representations of Sentences from Unlabelled Data](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-distributed-representations-sentences-unlabelled/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Felix Hill, Kyunghyun Cho, Anna Korhonen*2016 · 765 citations*
17. **[AdapterHub: A Framework for Adapting Transformers](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterhub-framework-adapting-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, et al.*2020 · 754 citations*
18. [**Passage Re-ranking with BERT arXiv:1901.04085**Rodrigo Nogueira, Kyunghyun Cho*2019 · 678 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2019-passage-re-ranking-bert/)
19. **[Asking and Answering Questions to Evaluate the Factual Consistency of Summaries ↗](https://aclanthology.org/2020.acl-main.450/) Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yet**Alex Wang, Kyunghyun Cho, Mike Lewis*2020 · 666 citations*
20. [**On Using Monolingual Corpora in Neural Machine Translation arXiv:1503.03535**Caglar Gulcehre, Orhan Firat, Kelvin Xu, et al.*2015 · 639 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2015-using-monolingual-corpora-neural-machine/)
21. **[Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement](https://md.research.elamur.ai/free/en/papers/lee-2018-deterministic-non-autoregressive-neural-sequence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jason Lee, Elman Mansimov, Kyunghyun Cho*2018 · 568 citations*
22. [**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/)
23. **[Fully Character-Level Neural Machine Translation without Explicit Segmentation](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jason Lee, Kyunghyun Cho, Thomas Hofmann*2017 · 553 citations*
24. **[Convolutional recurrent neural networks for music classification ↗](https://doi.org/10.1109/icassp.2017.7952585) IEEE International Conference on Acoustics Speech and Signal Processing · no summary yet**Keunwoo Choi et al.*2017 · 527 citations*
25. [**Neural Text Generation with Unlikelihood Training arXiv:1908.04319**Sean Welleck, Ilia Kulikov, Stephen Roller, et al.*2019 · 513 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2019-neural-text-generation-unlikelihood-training/)
26. **[Health system-scale language models are all-purpose prediction engines ↗](https://doi.org/10.1038/s41586-023-06160-y) Nature · no summary yet**Lavender Yao Jiang et al.*2023 · 472 citations*
27. **[Meta-Learning for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2018-meta-learning-low-resource-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiatao Gu, Yong Wang, Yun Chen, et al.*2018 · 456 citations*
28. **[Gated Feedback Recurrent Neural Networks ↗](https://arxiv.org/abs/1502.02367) arXiv (Cornell University) · no summary yet**Chung, Junyoung et al.*2015 · 438 citations*
29. [**Unsupervised Neural Machine Translation arXiv:1710.11041**Mikel Artetxe, Gorka Labaka, Eneko Agirre, et al.*2017 · 424 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2017-unsupervised-neural-machine-translation/)
30. **[End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results ↗](https://arxiv.org/abs/1412.1602) arXiv (Cornell University) · no summary yet**Jan Chorowski et al.*2014 · 416 citations*
31. **[A Character-level Decoder without Explicit Segmentation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chung-2016-character-level-decoder-without-explicit/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyoung Chung, Kyunghyun Cho, Yoshua Bengio*2016 · 413 citations*
32. [**True Few-Shot Learning with Language Models arXiv:2105.11447**Ethan Perez, Douwe Kiela, Kyunghyun Cho*2021 · 412 citations*](https://md.research.elamur.ai/free/en/papers/perez-2021-true-few-shot-learning-language/)
33. **[Dialogue Natural Language Inference](https://md.research.elamur.ai/free/en/papers/welleck-2019-dialogue-natural-language-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sean Welleck, Jason Weston, Arthur Szlam, et al.*2019 · 385 citations*
34. **[Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks ↗](https://doi.org/10.1109/tmm.2015.2477044) IEEE Transactions on Multimedia · no summary yet**Kyunghyun Cho, Aaron C. Courville, Yoshua Bengio*2015 · 361 citations*
35. **[Zero-Resource Translation with Multi-Lingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/firat-2016-zero-resource-translation-multi-lingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orhan Firat, Baskaran Sankaran, Yaser Al-onaizan, et al.*2016 · 356 citations*
36. **[Self-Rewarding Language Models ↗](https://arxiv.org/abs/2401.10020) arXiv:2401.10020 · no summary yet**Weizhe Yuan et al.*2024 · 338 citations*
37. [**Document Expansion by Query Prediction arXiv:1904.08375**Rodrigo Nogueira, Wei Yang, Jimmy Lin, et al.*2019 · 320 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2019-document-expansion-query-prediction/)
38. **[Multi-Stage Document Ranking with BERT ↗](https://arxiv.org/abs/1910.14424) arXiv (Cornell University) · no summary yet**Rodrigo Frassetto Nogueira et al.*2019 · 302 citations*
39. **[How to Construct Deep Recurrent Neural Networks ↗](https://arxiv.org/abs/1312.6026) arXiv:1312.6026 · no summary yet**Razvan Pascanu et al.*2013 · 302 citations*
40. **[Learning to Translate in Real-time with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2017-learning-translate-real-time-neural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiatao Gu, Graham Neubig, Kyunghyun Cho, et al.*2017 · 289 citations*
41. **[ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation ↗](https://doi.org/10.1109/cvprw.2016.60) IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · no summary yet**Francesco Visin et al.*2016 · 285 citations*
42. **[Zero-Shot Transfer Learning for Event Extraction](https://md.research.elamur.ai/free/en/papers/huang-2018-zero-shot-transfer-learning-event/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lifu Huang, Heng Ji, Kyunghyun Cho, et al.*2018 · 273 citations*
43. [**BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model arXiv:1902.04094**Alex Wang, Kyunghyun Cho*2019 · 256 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-bert-has-mouth-must-speak/)
44. **[Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative ↗](https://doi.org/10.1148/radiol.2020192091) Radiology · no summary yet**Kevin Leung et al.*2020 · 243 citations*
45. **[Search Engine Guided Neural Machine Translation ↗](https://doi.org/10.1609/aaai.v32i1.12013) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Jiatao Gu et al.*2018 · 240 citations*
46. **[Translation between Molecules and Natural Language](https://md.research.elamur.ai/free/en/papers/edwards-2022-translation-between-molecules-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Carl Edwards, Tuan Lai, Kevin Ros, et al.*2022 · 238 citations*
47. **[Learning to Understand Phrases by Embedding the Dictionary](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-understand-phrases-embedding-dictionary/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Felix Hill, Kyunghyun Cho, Anna Korhonen, et al.*2016 · 236 citations*
48. **[NIPS 2011 Workshop on Deep Learning and Unsupervised Feature Learning ↗](https://openalex.org/W2594481151) no summary yet**Kyunghyun Cho, Tapani Raiko, Alexander Ilin*2011 · 235 citations*
49. **[Neural Machine Translation with Byte-Level Subwords](https://md.research.elamur.ai/free/en/papers/wang-2019-neural-machine-translation-byte-level/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changhan Wang, Kyunghyun Cho, Jiatao Gu*2019 · 228 citations*
50. **[ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks ↗](https://arxiv.org/abs/1505.00393) arXiv (Cornell University) · no summary yet**Francesco Visin et al.*2015 · 228 citations*
51. **[Unsupervised Question Decomposition for Question Answering](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 222 citations*
52. **[Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training](https://md.research.elamur.ai/free/en/papers/li-2020-don-t-say-that-making/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Margaret Li, Stephen Roller, Ilia Kulikov, et al.*2020 · 217 citations*
53. **[Learning to Parse and Translate Improves Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/eriguchi-2017-learning-parse-translate-improves-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho*2017 · 217 citations*
54. **[The International Conference on Machine Learning (ICML 2011) ↗](https://openalex.org/W2596356468) no summary yet**Kyunghyun Cho, Tapani Raiko, Alexander Ilin*2011 · 215 citations*
55. **[An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization ↗](https://arxiv.org/abs/2002.07613) arXiv:2002.07613 · no summary yet**Yiqiu Shen et al.*2020 · 213 citations*
56. **[Can neural machine translation do simultaneous translation? ↗](https://arxiv.org/abs/1606.02012) arXiv (Cornell University) · no summary yet**Kyunghyun Cho, Masha Esipova*2016 · 209 citations*
57. **[Fine-grained attention mechanism for neural machine translation ↗](https://doi.org/10.1016/j.neucom.2018.01.007) Neurocomputing · no summary yet**Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio*2018 · 208 citations*
58. **[Nematus: a Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rico Sennrich, Orhan Firat, Kyunghyun Cho, et al.*2017 · 206 citations*
59. **[Conditional Molecular Design with Deep Generative Models ↗](https://doi.org/10.1021/acs.jcim.8b00263) Journal of Chemical Information and Modeling · no summary yet**Seokho Kang, Kyunghyun Cho*2018 · 202 citations*
60. **[Does Neural Machine Translation Benefit from Larger Context? ↗](https://arxiv.org/abs/1704.05135) arXiv:1704.05135 · no summary yet**Sebastien Jean et al.*2017 · 201 citations*
61. **[Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers ↗](https://arxiv.org/abs/1602.00367) arXiv (Cornell University) · no summary yet**Yijun Xiao, Kyunghyun Cho*2016 · 197 citations*
62. **[High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks ↗](https://arxiv.org/abs/1703.07047) arXiv (Cornell University) · no summary yet**Krzysztof J. Geras et al.*2017 · 193 citations*
63. **[Describing Videos by Exploiting Temporal Structure ↗](https://arxiv.org/abs/1502.08029) arXiv (Cornell University) · no summary yet**Yao, Li et al.*2015 · 193 citations*
64. **[Montreal Neural Machine Translation Systems for WMT'15 ↗](https://aclanthology.org/W15-3014/) Proceedings of the Tenth Workshop on Statistical Machine Translation · no summary yet**Sébastien Jean et al.*2015 · 185 citations*
65. **[Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models ↗](https://arxiv.org/abs/1909.11299) arXiv (Cornell University) · no summary yet**Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang*2019 · 173 citations*
66. **[Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines ↗](https://doi.org/10.1007/978-3-642-21735-7_2) Lecture notes in computer science · no summary yet**Kyunghyun Cho, Alexander Ilin, Tapani Raiko*2011 · 172 citations*
67. **[Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks ↗](https://doi.org/10.1007/978-3-662-44848-9_34) Lecture notes in computer science · no summary yet**Çağlar Gülçehre et al.*2014 · 171 citations*
68. **[Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations](https://md.research.elamur.ai/free/en/papers/gu-2019-improved-zero-shot-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatao Gu, Yong Wang, Kyunghyun Cho, et al.*2019 · 162 citations*
69. **[SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness](https://md.research.elamur.ai/free/en/papers/ng-2020-ssmba-self-supervised-manifold-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi*2020 · 161 citations*
70. **[Task-Oriented Query Reformulation with Reinforcement Learning ↗](https://aclanthology.org/D17-1061/) Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing · no summary yet**Rodrigo Nogueira, Kyunghyun Cho*2017 · 161 citations*
71. **[Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior ↗](https://doi.org/10.1609/aaai.v34i05.6413) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Raphael Shu et al.*2020 · 159 citations*
72. **[Iterative Reasoning Preference Optimization](https://md.research.elamur.ai/free/en/papers/pang-2024-iterative-reasoning-preference-optimization/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.*2024 · 153 citations*
73. **[Dynamic Meta-Embeddings for Improved Sentence Representations ↗](https://aclanthology.org/D18-1176/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Douwe Kiela, Changhan Wang, Kyunghyun Cho*2018 · 150 citations*
74. **[On integrating a language model into neural machine translation ↗](https://doi.org/10.1016/j.csl.2017.01.014) Computer Speech & Language · no summary yet**Çağlar Gülçehre et al.*2017 · 148 citations*
75. **[Protein remote homology detection and structural alignment using deep learning ↗](https://doi.org/10.1038/s41587-023-01917-2) Nature Biotechnology · no summary yet**Tymor Hamamsy et al.*2023 · 145 citations*
76. **[Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks ↗](https://doi.org/10.1038/s41598-018-34817-6) Scientific Reports · no summary yet**Cem M. Deniz et al.*2018 · 140 citations*
77. **[Molecular Geometry Prediction using a Deep Generative Graph Neural Network ↗](https://doi.org/10.1038/s41598-019-56773-5) Scientific Reports · no summary yet**Elman Mansimov et al.*2019 · 135 citations*
78. **[DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder ↗](https://arxiv.org/abs/1805.12352) arXiv (Cornell University) · no summary yet**Xiaodong Gu et al.*2018 · 132 citations*
79. **[Transfer learning for music classification and regression tasks ↗](https://arxiv.org/abs/1703.09179) arXiv (Cornell University) · no summary yet**Keunwoo Choi et al.*2017 · 130 citations*
80. **[QCD-aware recursive neural networks for jet physics ↗](https://doi.org/10.1007/jhep01(2019)057) Journal of High Energy Physics · no summary yet**Gilles Louppe et al.*2017 · 127 citations*
81. **[Gated Word-Character Recurrent Language Model ↗](https://aclanthology.org/D16-1209/) Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing · no summary yet**Yasumasa Miyamoto, Kyunghyun Cho*2016 · 126 citations*
82. **[Insertion-based Decoding with Automatically Inferred Generation Order](https://md.research.elamur.ai/free/en/papers/gu-2019-insertion-based-decoding-automatically-inferred/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiatao Gu, Qi Liu, Kyunghyun Cho*2019 · 125 citations*
83. **[Importance of Search and Evaluation Strategies in Neural Dialogue Modeling](https://md.research.elamur.ai/free/en/papers/kulikov-2019-importance-search-evaluation-strategies-neural/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Ilia Kulikov, Alexander Miller, Kyunghyun Cho, et al.*2019 · 121 citations*
84. **[Query-Efficient Imitation Learning for End-to-End Autonomous Driving ↗](https://arxiv.org/abs/1605.06450) arXiv (Cornell University) · no summary yet**Jiakai Zhang, Kyunghyun Cho*2016 · 120 citations*
85. **[Connecting the Dots: Event Graph Schema Induction with Path Language Modeling ↗](https://aclanthology.org/2020.emnlp-main.50/) Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yet**Manling Li et al.*2020 · 119 citations*
86. **[Context-dependent word representation for neural machine translation ↗](https://doi.org/10.1016/j.csl.2017.01.007) Computer Speech & Language · no summary yet**Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio*2017 · 118 citations*
87. **[Multi-way, multilingual neural machine translation ↗](https://doi.org/10.1016/j.csl.2016.10.006) Computer Speech & Language · no summary yet**Orhan Fırat et al.*2016 · 114 citations*
88. **[Boundary-Seeking Generative Adversarial Networks ↗](https://arxiv.org/abs/1702.08431) arXiv (Cornell University) · no summary yet**R Devon Hjelm et al.*2017 · 113 citations*
89. **[Query-Efficient Imitation Learning for End-to-End Simulated Driving ↗](https://doi.org/10.1609/aaai.v31i1.10857) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Jiakai Zhang, Kyunghyun Cho*2017 · 104 citations*
90. **[Generalized Inner Loop Meta-Learning ↗](https://arxiv.org/abs/1910.01727) arXiv (Cornell University) · no summary yet**Edward Grefenstette et al.*2019 · 101 citations*
91. **[Non-Monotonic Sequential Text Generation ↗](https://arxiv.org/abs/1902.02192) arXiv (Cornell University) · no summary yet**Sean Welleck et al.*2019 · 101 citations*
92. **[Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation ↗](https://aclanthology.org/W14-4009/) Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation · no summary yet**Jean Pouget-Abadie et al.*2014 · 96 citations*
93. **[Masked graph modeling for molecule generation ↗](https://doi.org/10.1038/s41467-021-23415-2) Nature Communications · no summary yet**Omar Mahmood et al.*2021 · 94 citations*
94. **[Continual Learning via Neural Pruning ↗](https://arxiv.org/abs/1903.04476) arXiv (Cornell University) · no summary yet**Siavash Golkar, M. Kagan, Kyunghyun Cho*2019 · 90 citations*
95. **[A study of the recurrent neural network encoder-decoder for large vocabulary speech recognition ↗](https://doi.org/10.21437/interspeech.2015-654) Interspeech (USB) · no summary yet**Liang Lu et al.*2015 · 90 citations*
96. **[Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search ↗](https://aclanthology.org/2021.acl-long.508/) Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yet**Gyuwan Kim, Kyunghyun Cho*2021 · 88 citations*
97. **[The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction ↗](https://aclanthology.org/2021.emnlp-main.422/) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · no summary yet**Manling Li et al.*2021 · 87 citations*
98. **[Training Language Models with Language Feedback at Scale ↗](https://arxiv.org/abs/2303.16755) arXiv:2303.16755 · no summary yet**Jérémy Scheurer et al.*2023 · 85 citations*
99. **[Learning Distributed Representations from Reviews for Collaborative Filtering ↗](https://doi.org/10.1145/2792838.2800192) ACM Conference on Recommender Systems (RecSys) · no summary yet**Amjad Almahairi et al.*2015 · 85 citations*
100. **[Breast Density Classification with Deep Convolutional Neural Networks ↗](https://doi.org/10.1109/icassp.2018.8462671) IEEE International Conference on Acoustics Speech and Signal Processing · no summary yet**Nan Wu et al.*2018 · 84 citations*

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