--- title: "Who cites A Fast and Simple Algorithm for — 113 citing papers" description: "113 papers of the Elamur Research library cite «A Fast and Simple Algorithm for Training Neural Probabilistic Language Models», found in their…" canonical: "https://research.elamur.ai/free/en/papers/mnih-2012-fast-simple-algorithm-training-neural/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/mnih-2012-fast-simple-algorithm-training-neural/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [A Fast and Simple Algorithm for Training Neural…](https://md.research.elamur.ai/free/en/papers/mnih-2012-fast-simple-algorithm-training-neural/) / cited by # Who cites «A Fast and Simple Algorithm for Training Neural Probabilistic Language Models» 113 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «A Fast and Simple Algorithm for Training Neural Probabilistic Language Models»](https://md.research.elamur.ai/free/en/papers/mnih-2012-fast-simple-algorithm-training-neural/) 1. [**Efficient Estimation of Word Representations in Vector Space arXiv:1301.3781**Tomas Mikolov, Kai Chen, Greg Corrado, et al.*2013 · 28,759 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-efficient-estimation-word-representations-vector/) 2. [**Distributed Representations of Words and Phrases and their Compositionality arXiv:1310.4546**Tomas Mikolov, Ilya Sutskever, Kai Chen, et al.*2013 · 21,623 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-distributed-representations-words-phrases-their/) 3. [**Representation Learning with Contrastive Predictive Coding arXiv:1807.03748**Aaron van den Oord, Yazhe Li, Oriol Vinyals*2018 · 7,022 citations*](https://md.research.elamur.ai/free/en/papers/oord-2018-representation-learning-contrastive-predictive-coding/) 4. **[From Captions to Visual Concepts and Back](https://md.research.elamur.ai/free/en/papers/fang-2014-captions-visual-concepts-back/) [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/)**Hao Fang, Saurabh Gupta, Forrest Iandola, et al.*2014 · 1,450 citations* 5. **[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* 6. **[Improving Lexical Embeddings with Semantic Knowledge](https://md.research.elamur.ai/free/en/papers/yu-2014-improving-lexical-embeddings-semantic-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mo Yu, Mark Dredze*2014 · 371 citations* 7. **[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* 8. **[Decoding with Large-Scale Neural Language Models Improves Translation](https://md.research.elamur.ai/free/en/papers/vaswani-2013-decoding-large-scale-neural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ashish Vaswani, Yinggong Zhao, Victoria Fossum, et al.*2013 · 318 citations* 9. [**Efficient softmax approximation for GPUs arXiv:1609.04309**Edouard Grave, Armand Joulin, Moustapha Cisse, et al.*2016 · 205 citations*](https://md.research.elamur.ai/free/en/papers/grave-2016-efficient-softmax-approximation-gpus/) 10. [**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/) 11. **[Scaling Deep Contrastive Learning Batch Size under Memory Limited Setup](https://md.research.elamur.ai/free/en/papers/gao-2021-scaling-deep-contrastive-learning-batch/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Luyu Gao, Yunyi Zhang, Jiawei Han, et al.*2021 · 131 citations* 12. [**Online normalizer calculation for softmax arXiv 2018 (NVIDIA)**Maxim Milakov, Natalia Gimelshein*2018 · 123 citations*](https://md.research.elamur.ai/free/en/papers/milakov-2018-online-normalizer-calculation-softmax/) 13. [**Probabilistic Modelling of Morphologically Rich Languages**Jan A. Botha*2015 · 4 citations*](https://md.research.elamur.ai/free/en/papers/botha-2015-probabilistic-modelling-morphologically-rich-languages/) 14. **[Algorithmes à base d'échantillonage pour l'entraînement de modèles de langue neuronaux (Here the title in English)](https://md.research.elamur.ai/free/en/papers/labeau-2018-algorithmes-base-d-echantillonage-pour/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Matthieu Labeau, Alexandre Allauzen*2018* 99 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/mnih-2012-fast-simple-algorithm-training-neural/) — A Fast and Simple Algorithm for Training Neural Probabilistic Language Models