---
title: "Who cites Frédéric Bastien — 327 papers of our library"
description: "327 papers of the Elamur Research library cite the works of Frédéric Bastien, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/frederic-bastien/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/frederic-bastien/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Frédéric Bastien](https://md.research.elamur.ai/free/en/authors/frederic-bastien/) / cited by

# Who cites Frédéric Bastien

328 citations of their works from 327 papers of our library (of the 149,439 whose bibliographies we read) · 52 with a page here, the most cited first · [← Frédéric Bastien](https://md.research.elamur.ai/free/en/authors/frederic-bastien/)

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. [**PyTorch: An Imperative Style, High-Performance Deep Learning Library arXiv:1912.01703**Adam Paszke, Sam Gross, Francisco Massa, et al.*2019 · 18,645 citations*](https://md.research.elamur.ai/free/en/papers/paszke-2019-pytorch-imperative-style-high-performance/)
4. [**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/)
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. [**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/)
7. [**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/)
8. [**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/)
9. [**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/)
10. [**Layer Normalization arXiv:1607.06450**Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton*2016 · 1,819 citations*](https://md.research.elamur.ai/free/en/papers/ba-2016-layer-normalization/)
11. [**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/)
12. [**A Structured Self-attentive Sentence Embedding arXiv:1703.03130**Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.*2017 · 1,797 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/)
13. [**The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables arXiv:1611.00712**Chris J. Maddison, Andriy Mnih, Yee Whye Teh*2016 · 1,629 citations*](https://md.research.elamur.ai/free/en/papers/maddison-2016-concrete-distribution-continuous-relaxation-discrete/)
14. [**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/)
15. [**Understanding Black-box Predictions via Influence Functions arXiv:1703.04730**Pang Wei Koh, Percy Liang*2017 · 1,514 citations*](https://md.research.elamur.ai/free/en/papers/koh-2017-understanding-black-box-predictions-influence/)
16. [**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/)
17. **[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*
18. **[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*
19. [**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/)
20. **[PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation](https://md.research.elamur.ai/free/en/papers/ansel-2024-pytorch-2-faster-machine-learning/) [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/)**Jason Ansel, Edward Yang, Horace He, et al.*2024 · 946 citations*
21. **[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*
22. **[Pointing the Unknown Words](https://md.research.elamur.ai/free/en/papers/gulcehre-2016-pointing-unknown-words/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, et al.*2016 · 651 citations*
23. **[Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm](https://md.research.elamur.ai/free/en/papers/felbo-2017-millions-emoji-occurrences-learn-any/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bjarke Felbo, Alan Mislove, Anders Søgaard, et al.*2017 · 621 citations*
24. **[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*
25. **[Cross-Sentence N-ary Relation Extraction with Graph LSTMs](https://md.research.elamur.ai/free/en/papers/peng-2017-cross-sentence-n-ary-relation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nanyun Peng, Hoifung Poon, Chris Quirk, et al.*2017 · 557 citations*
26. **[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*
27. **[EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/mageed-2017-emonet-fine-grained-emotion-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Muhammad Abdul-Mageed, Lyle Ungar*2017 · 487 citations*
28. **[Gated-Attention Readers for Text Comprehension](https://md.research.elamur.ai/free/en/papers/dhingra-2016-gated-attention-readers-text-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhuwan Dhingra, Hanxiao Liu, Zhilin Yang, et al.*2016 · 463 citations*
29. **[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*
30. **[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*
31. **[Semi-supervised Multitask Learning for Sequence Labeling](https://md.research.elamur.ai/free/en/papers/rei-2017-semi-supervised-multitask-learning-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marek Rei*2017 · 347 citations*
32. **[Neural Paraphrase Generation with Stacked Residual LSTM Networks](https://md.research.elamur.ai/free/en/papers/prakash-2016-neural-paraphrase-generation-stacked-residual/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Aaditya Prakash, Sadid A. Hasan, Kathy Lee, et al.*2016 · 337 citations*
33. [**An Actor-Critic Algorithm for Sequence Prediction arXiv:1607.07086**Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, et al.*2016 · 335 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2016-actor-critic-algorithm-sequence-prediction/)
34. [**Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions arXiv:1802.04730**Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.*2018 · 323 citations*](https://md.research.elamur.ai/free/en/papers/vasilache-2018-tensor-comprehensions-framework-agnostic-high/)
35. [**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/)
36. [**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/)
37. [**DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines arXiv:2310.03714**Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/khattab-2023-dspy-compiling-declarative-language-model/)
38. [**Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning OSDI 2022**Lianmin Zheng, Zhuohan Li, Hao Zhang, et al.*2022 · 279 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-alpa-automating-inter-intra-operator/)
39. [**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/)
40. **[Charagram: Embedding Words and Sentences via Character n-grams](https://md.research.elamur.ai/free/en/papers/wieting-2016-charagram-embedding-words-sentences-character/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2016 · 242 citations*
41. **[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*
42. **[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*
43. [**A Neural Knowledge Language Model arXiv:1608.00318**Sungjin Ahn, Heeyoul Choi, Tanel Pärnamaa, et al.*2016 · 146 citations*](https://md.research.elamur.ai/free/en/papers/ahn-2016-neural-knowledge-language-model/)
44. [**Continuously Learning Neural Dialogue Management arXiv:1606.02689**Pei-Hao Su, Milica Gasic, Nikola Mrksic, et al.*2016 · 137 citations*](https://md.research.elamur.ai/free/en/papers/su-2016-continuously-learning-neural-dialogue-management/)
45. **[Learning Distributed Representations of Texts and Entities from Knowledge Base](https://md.research.elamur.ai/free/en/papers/yamada-2017-learning-distributed-representations-texts-entities/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2017 · 125 citations*
46. **[A Systematic Study of Neural Discourse Models for Implicit Discourse Relation](https://md.research.elamur.ai/free/en/papers/rutherford-2017-systematic-study-neural-discourse-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Attapol Rutherford, Vera Demberg, Nianwen Xue*2017 · 78 citations*
47. **[Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/iida-2016-intra-sentential-subject-zero-anaphora/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryu Iida, Kentaro Torisawa, Jong-Hoon Oh, et al.*2016 · 51 citations*
48. **[Robust Non-Explicit Neural Discourse Parser in English and Chinese](https://md.research.elamur.ai/free/en/papers/rutherford-2016-robust-non-explicit-neural-discourse/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Attapol Rutherford, Nianwen Xue*2016 · 41 citations*
49. **[Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution](https://md.research.elamur.ai/free/en/papers/liu-2017-generating-exploiting-large-scale-pseudo/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ting Liu, Yiming Cui, Qingyu Yin, et al.*2017 · 37 citations*
50. **[The DCU Discourse Parser for Connective, Argument Identification and Explicit Sense Classification](https://md.research.elamur.ai/free/en/papers/wang-2015-dcu-discourse-parser-connective-argument/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Longyue Wang, Chris Hokamp, Tsuyoshi Okita, et al.*2015 · 18 citations*
51. **[Recognizing Textual Entailment in Twitter Using Word Embeddings](https://md.research.elamur.ai/free/en/papers/sulea-2017-recognizing-textual-entailment-twitter-word/) [Workshop on Evaluating Vector Space Representations for NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-evaluating-vector-space-representations-for-nlp/)**Octavia-Maria Şulea*2017 · 7 citations*
52. [**Detecting Interrogative Utterances with Recurrent Neural Networks arXiv:1511.01042**Junyoung Chung, Jacob Devlin, Hany Hassan Awadalla*2015*](https://md.research.elamur.ai/free/en/papers/chung-2015-detecting-interrogative-utterances-recurrent-neural/)

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

- [← back to](https://md.research.elamur.ai/free/en/authors/frederic-bastien/) — Frédéric Bastien
