---
title: "Who cites Jan Koutnik — 173 papers of our library"
description: "173 papers of the Elamur Research library cite the works of Jan Koutnik, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jan-koutnik/cited-by/"
---
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# Who cites Jan Koutnik

178 citations of their works from 173 papers of our library (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · [← Jan Koutnik](https://md.research.elamur.ai/free/en/authors/jan-koutnik/)

1. [**Character-level Convolutional Networks for Text Classification arXiv:1509.01626**Xiang Zhang, Junbo Zhao, Yann LeCun*2015 · 4,827 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2015-character-level-convolutional-networks-text/)
2. [**Neural Architecture Search with Reinforcement Learning arXiv:1611.01578**Barret Zoph, Quoc V. Le*2016 · 4,413 citations*](https://md.research.elamur.ai/free/en/papers/zoph-2016-neural-architecture-search-reinforcement-learning/)
3. [**Pointer Sentinel Mixture Models arXiv:1609.07843**Stephen Merity, Caiming Xiong, James Bradbury, et al.*2016 · 1,733 citations*](https://md.research.elamur.ai/free/en/papers/merity-2016-pointer-sentinel-mixture-models/)
4. **[Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, et al.*2018 · 1,522 citations*
5. **[Generation and Comprehension of Unambiguous Object Descriptions](https://md.research.elamur.ai/free/en/papers/mao-2015-generation-comprehension-unambiguous-object-descriptions/) [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/)**Junhua Mao, Jonathan Huang, Alexander Toshev, et al.*2015 · 1,388 citations*
6. [**Deep Biaffine Attention for Neural Dependency Parsing**Timothy Dozat, Christopher D. Manning*2016 · 1,326 citations*](https://md.research.elamur.ai/free/en/papers/dozat-2016-deep-biaffine-attention-neural-dependency/)
7. **[A Primer on Neural Network Models for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/goldberg-2015-primer-neural-network-models-natural/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Yoav Goldberg*2015 · 1,303 citations*
8. **[Neural Responding Machine for Short-Text Conversation](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,257 citations*
9. **[Modeling Context in Referring Expressions](https://md.research.elamur.ai/free/en/papers/yu-2016-modeling-context-referring-expressions/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Licheng Yu, Patrick Poirson, Shan Yang, et al.*2016 · 1,203 citations*
10. [**Visualizing and Understanding Recurrent Networks arXiv:1506.02078**Andrej Karpathy, Justin Johnson, Li Fei-Fei*2015 · 954 citations*](https://md.research.elamur.ai/free/en/papers/karpathy-2015-visualizing-understanding-recurrent-networks/)
11. **[Using the Output Embedding to Improve Language Models](https://md.research.elamur.ai/free/en/papers/press-2017-output-embedding-improve-language-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ofir Press, Lior Wolf*2017 · 909 citations*
12. [**Efficient Neural Architecture Search via Parameter Sharing arXiv:1802.03268**Hieu Pham, Melody Y. Guan, Barret Zoph, et al.*2018 · 699 citations*](https://md.research.elamur.ai/free/en/papers/pham-2018-efficient-neural-architecture-search-parameter/)
13. [**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/)
14. **[Massive Exploration of Neural Machine Translation Architectures](https://md.research.elamur.ai/free/en/papers/britz-2017-massive-exploration-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Denny Britz, Anna Goldie, Minh-Thang Luong, et al.*2017 · 574 citations*
15. [**Deep Learning Scaling is Predictable, Empirically arXiv:1712.00409**Joel Hestness, Sharan Narang, Newsha Ardalani, et al.*2017 · 518 citations*](https://md.research.elamur.ai/free/en/papers/hestness-2017-deep-learning-scaling-predictable-empirically/)
16. [**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/)
17. [**Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling arXiv:1611.01462**Hakan Inan, Khashayar Khosravi, Richard Socher*2016 · 414 citations*](https://md.research.elamur.ai/free/en/papers/inan-2016-tying-word-vectors-word-classifiers/)
18. **[Improved Transition-based Parsing by Modeling Characters instead of Words with LSTMs](https://md.research.elamur.ai/free/en/papers/ballesteros-2015-improved-transition-based-parsing-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miguel Ballesteros, Chris Dyer, Noah A. Smith*2015 · 403 citations*
19. **[An Analysis of Encoder Representations in Transformer-Based Machine Translation](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Alessandro Raganato, Jörg Tiedemann*2018 · 369 citations*
20. [**Compressive Transformers for Long-Range Sequence Modelling arXiv:1911.05507**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
21. **[On the Practical Computational Power of Finite Precision RNNs for Language Recognition](https://md.research.elamur.ai/free/en/papers/weiss-2018-practical-computational-power-finite-precision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gail Weiss, Yoav Goldberg, Eran Yahav*2018 · 313 citations*
22. **[xLSTM: Extended Long Short-Term Memory](https://md.research.elamur.ai/free/en/papers/beck-2024-xlstm-extended-long-short-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.*2024 · 296 citations*
23. [**Hierarchical Multiscale Recurrent Neural Networks arXiv:1609.01704**Junyoung Chung, Sungjin Ahn, Yoshua Bengio*2016 · 288 citations*](https://md.research.elamur.ai/free/en/papers/chung-2016-hierarchical-multiscale-recurrent-neural-networks/)
24. **[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*
25. [**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/)
26. [**Recurrent Highway Networks arXiv:1607.03474**Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnik, et al.*2016 · 147 citations*](https://md.research.elamur.ai/free/en/papers/zilly-2016-recurrent-highway-networks/)
27. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
28. **[Character-Level Language Modeling with Deeper Self-Attention](https://md.research.elamur.ai/free/en/papers/al-rfou-2018-character-level-language-modeling-deeper/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Rami Al-Rfou, Dokook Choe, Noah Constant, et al.*2018 · 138 citations*
29. **[Data Augmentation for Morphological Reinflection](https://md.research.elamur.ai/free/en/papers/silfverberg-2017-data-augmentation-morphological-reinflection/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Miikka Silfverberg, Adam Wiemerslage, Ling Liu, et al.*2017 · 122 citations*
30. **[Unified Pragmatic Models for Generating and Following Instructions](https://md.research.elamur.ai/free/en/papers/fried-2018-unified-pragmatic-models-generating-following/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Daniel Fried, Jacob Andreas, Dan Klein*2018 · 115 citations*
31. [**Universal Dependencies Parsing for Colloquial Singaporean English**Hongmin Wang, Yue Zhang, GuangYong Leonard Chan, et al.*2017 · 49 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-universal-dependencies-parsing-colloquial-singaporean/)
32. **[A Transformer Approach to Contextual Sarcasm Detection in Twitter](https://md.research.elamur.ai/free/en/papers/gregory-2020-transformer-approach-contextual-sarcasm-detection/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Hunter Gregory, Steven Li, Pouya Mohammadi, et al.*2020 · 38 citations*
33. **[Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysis](https://md.research.elamur.ai/free/en/papers/nassif-2021-empirical-evaluation-shallow-deep-learning/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Ali Bou Nassif, Abdollah Masoud Darya, Ashraf Elnagar*2021 · 34 citations*

140 more citing papers of our library have no page here yet.

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