---
title: "Who cites Ludovic Denoyer — 572 papers of our library"
description: "572 papers of the Elamur Research library cite the works of Ludovic Denoyer, found in their bibliographies; the most cited first."
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---
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# Who cites Ludovic Denoyer

584 citations of their works from 572 papers of our library (of the 141,840 whose bibliographies we read) · 63 with a page here, the most cited first · [← Ludovic Denoyer](https://md.research.elamur.ai/free/en/authors/ludovic-denoyer/)

1. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,886 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/)
2. [**Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates**Taku Kudo*2018 · 1,566 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2018-subword-regularization-improving-neural-network/)
3. [**Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation**Nils Reimers, Iryna Gurevych*2020 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2020-making-monolingual-sentence-embeddings-multilingual/)
4. [**CTRL: A Conditional Transformer Language Model for Controllable Generation**Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.*2019 · 1,280 citations*](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/)
5. [**MASS: Masked Sequence to Sequence Pre-training for Language Generation**Kaitao Song, Xu Tan, Tao Qin, et al.*2019 · 1,127 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/)
6. [**ImageBind: One Embedding Space To Bind Them All**Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, et al.*2023 · 943 citations*](https://md.research.elamur.ai/free/en/papers/girdhar-2023-imagebind-one-embedding-space-bind/)
7. [**Achieving Human Parity on Automatic Chinese to English News Translation**Hany Hassan, Anthony Aue, Chang Chen, et al.*2018 · 797 citations*](https://md.research.elamur.ai/free/en/papers/hassan-2018-achieving-human-parity-automatic-chinese/)
8. [**MLQA: Evaluating Cross-lingual Extractive Question Answering**Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al.*2019 · 738 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/)
9. [**Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges**Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al.*2019 · 556 citations*](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/)
10. [**Style Transfer Through Back-Translation**Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, et al.*2018 · 555 citations*](https://md.research.elamur.ai/free/en/papers/prabhumoye-2018-style-transfer-through-back-translation/)
11. [**Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement**Jason Lee, Elman Mansimov, Kyunghyun Cho*2018 · 551 citations*](https://md.research.elamur.ai/free/en/papers/lee-2018-deterministic-non-autoregressive-neural-sequence/)
12. [**Meta-Learning for Low-Resource Neural Machine Translation**Jiatao Gu, Yong Wang, Yun Chen, et al.*2018 · 454 citations*](https://md.research.elamur.ai/free/en/papers/gu-2018-meta-learning-low-resource-neural/)
13. [**Unsupervised Statistical Machine Translation**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2018 · 433 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-unsupervised-statistical-machine-translation/)
14. [**Event Extraction as Machine Reading Comprehension**Jian Liu, Yubo Chen, Kang Liu, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/liu-2020-event-extraction-as-machine-reading/)
15. [**Multilingual and Multi-Aspect Hate Speech Analysis**Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, et al.*2019 · 410 citations*](https://md.research.elamur.ai/free/en/papers/ousidhoum-2019-multilingual-multi-aspect-hate-speech/)
16. [**True Few-Shot Learning with Language Models**Ethan Perez, Douwe Kiela, Kyunghyun Cho*2021 · 404 citations*](https://md.research.elamur.ai/free/en/papers/perez-2021-true-few-shot-learning-language/)
17. [**On the Limitations of Unsupervised Bilingual Dictionary Induction**Anders Søgaard, Sebastian Ruder, Ivan Vulić*2018 · 398 citations*](https://md.research.elamur.ai/free/en/papers/sogaard-2018-limitations-unsupervised-bilingual-dictionary-induction/)
18. [**Disentangled Representation Learning for Non-Parallel Text Style Transfer**Vineet John, Lili Mou, Hareesh Bahuleyan, et al.*2019 · 397 citations*](https://md.research.elamur.ai/free/en/papers/john-2019-disentangled-representation-learning-non-parallel/)
19. [**BPE-Dropout: Simple and Effective Subword Regularization**Ivan Provilkov, Dmitrii Emelianenko, Elena Voita*2020 · 389 citations*](https://md.research.elamur.ai/free/en/papers/provilkov-2020-bpe-dropout-simple-effective-subword/)
20. [**The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English**Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al.*2019 · 363 citations*](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/)
21. [**Universal Neural Machine Translation for Extremely Low Resource Languages**Jiatao Gu, Hany Hassan, Jacob Devlin, et al.*2018 · 358 citations*](https://md.research.elamur.ai/free/en/papers/gu-2018-universal-neural-machine-translation-extremely/)
22. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
23. [**Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer**Juncen Li, Robin Jia, He He, et al.*2018 · 347 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-delete-retrieve-generate-simple-approach/)
24. [**Gromov-Wasserstein Alignment of Word Embedding Spaces**David Alvarez-Melis, Tommi Jaakkola*2018 · 337 citations*](https://md.research.elamur.ai/free/en/papers/melis-2018-gromov-wasserstein-alignment-word-embedding/)
25. [**Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing**Tal Schuster, Ori Ram, Regina Barzilay, et al.*2019 · 295 citations*](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/)
26. [**PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/)
27. [**A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer**Fuli Luo, Peng Li, Jie Zhou, et al.*2019 · 266 citations*](https://md.research.elamur.ai/free/en/papers/luo-2019-dual-reinforcement-learning-framework-unsupervised/)
28. [**Contrastive Learning for Many-to-many Multilingual Neural Machine Translation**Xiao Pan, Mingxuan Wang, Liwei Wu, et al.*2021 · 256 citations*](https://md.research.elamur.ai/free/en/papers/pan-2021-contrastive-learning-many-many-multilingual/)
29. [**An Empirical Survey of Data Augmentation for Limited Data Learning in NLP**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)
30. [**Towards Robust Neural Machine Translation**Yong Cheng, Zhaopeng Tu, Fandong Meng, et al.*2018 · 237 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2018-robust-neural-machine-translation/)
31. [**How Context Affects Language Models' Factual Predictions**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 231 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/)
32. [**Unsupervised Question Decomposition for Question Answering**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 218 citations*](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/)
33. [**Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer**Cicero Nogueira dos Santos, Igor Melnyk, Inkit Padhi*2018 · 210 citations*](https://md.research.elamur.ai/free/en/papers/santos-2018-fighting-offensive-language-social-media/)
34. [**Training Question Answering Models From Synthetic Data**Raul Puri, Ryan Spring, Mohammad Shoeybi, et al.*2020 · 206 citations*](https://md.research.elamur.ai/free/en/papers/puri-2020-training-question-answering-models-synthetic/)
35. [**Contextual Parameter Generation for Universal Neural Machine Translation**Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig, et al.*2018 · 205 citations*](https://md.research.elamur.ai/free/en/papers/platanios-2018-contextual-parameter-generation-universal-neural/)
36. [**An Effective Approach to Unsupervised Machine Translation**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2019 · 203 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2019-effective-approach-unsupervised-machine-translation/)
37. [**Autoformalization with Large Language Models**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/)
38. [**Unsupervised Question Answering by Cloze Translation**Patrick Lewis, Ludovic Denoyer, Sebastian Riedel*2019 · 192 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2019-unsupervised-question-answering-cloze-translation/)
39. [**Pre-training via Paraphrasing**Mike Lewis, Marjan Ghazvininejad, Gargi Ghosh, et al.*2020 · 181 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-pre-training-paraphrasing/)
40. [**Pre-training Multilingual Neural Machine Translation by Leveraging Alignment Information**Zehui Lin, Xiao Pan, Mingxuan Wang, et al.*2020 · 178 citations*](https://md.research.elamur.ai/free/en/papers/lin-2020-pre-training-multilingual-neural-machine/)
41. [**Generalized Data Augmentation for Low-Resource Translation**Mengzhou Xia, Xiang Kong, Antonios Anastasopoulos, et al.*2019 · 177 citations*](https://md.research.elamur.ai/free/en/papers/xia-2019-generalized-data-augmentation-low-resource/)
42. [**Soft Contextual Data Augmentation for Neural Machine Translation**Fei Gao, Jinhua Zhu, Lijun Wu, et al.*2019 · 172 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-soft-contextual-data-augmentation-neural/)
43. [**Style Transfer as Unsupervised Machine Translation**Zhirui Zhang, Shuo Ren, Shujie Liu, et al.*2018 · 164 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-style-transfer-unsupervised-machine-translation/)
44. [**AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages**Abteen Ebrahimi, Manuel Mager, Arturo Oncevay, et al.*2022 · 163 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2022-americasnli-evaluating-zero-shot-natural/)
45. [**Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations**Jiatao Gu, Yong Wang, Kyunghyun Cho, et al.*2019 · 162 citations*](https://md.research.elamur.ai/free/en/papers/gu-2019-improved-zero-shot-neural-machine/)
46. [**Understanding tables with intermediate pre-training**Julian Eisenschlos, Syrine Krichene, Thomas Müller*2020 · 158 citations*](https://md.research.elamur.ai/free/en/papers/eisenschlos-2020-understanding-tables-intermediate-pre-training/)
47. [**Unsupervised Translation of Programming Languages**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 158 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/)
48. [**Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?**Ivan Vulić, Goran Glavaš, Roi Reichart, et al.*2019 · 157 citations*](https://md.research.elamur.ai/free/en/papers/vulic-2019-do-we-really-need-fully/)
49. [**Unsupervised Text Style Transfer using Language Models as Discriminators**Zichao Yang, Zhiting Hu, Chris Dyer, et al.*2018 · 157 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-unsupervised-text-style-transfer-using/)
50. [**A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation**David Ifeoluwa Adelani, Jesujoba Oluwadara Alabi, Angela Fan, et al.*2022 · 155 citations*](https://md.research.elamur.ai/free/en/papers/adelani-2022-few-thousand-translations-go-long/)
51. [**ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics**Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-proofnet-autoformalizing-formally-proving-undergraduate/)
52. [**Pushing the Limits of Low-Resource Morphological Inflection**Antonios Anastasopoulos, Graham Neubig*2019 · 137 citations*](https://md.research.elamur.ai/free/en/papers/anastasopoulos-2019-pushing-limits-low-resource-morphological/)
53. [**ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora**Xuan Ouyang, Shuohuan Wang, Chao Pang, et al.*2020 · 127 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2020-ernie-m-enhanced-multilingual/)
54. [**Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus**Isaac Caswell, Theresa Breiner, Daan van Esch, et al.*2020 · 111 citations*](https://md.research.elamur.ai/free/en/papers/caswell-2020-language-id-wild-unexpected/)
55. [**Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation**Aditya Siddhant, Ankur Bapna, Yuan Cao, et al.*2020 · 108 citations*](https://md.research.elamur.ai/free/en/papers/siddhant-2020-leveraging-monolingual-data-self-supervision/)
56. [**APE at Scale and Its Implications on MT Evaluation Biases**Markus Freitag, Isaac Caswell, Scott Roy*2019 · 107 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2019-ape-scale-its-implications-mt/)
57. [**Exploiting Monolingual Data at Scale for Neural Machine Translation**Lijun Wu, Yiren Wang, Yingce Xia, et al.*2019 · 102 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-exploiting-monolingual-data-scale-neural/)
58. [**How to Adapt Your Pretrained Multilingual Model to 1600 Languages**Abteen Ebrahimi, Katharina Kann*2021 · 86 citations*](https://md.research.elamur.ai/free/en/papers/ebrahimi-2021-how-adapt-your-pretrained-multilingual/)
59. [**Evaluating prose style transfer with the Bible**Keith Carlson, Allen Riddell, Daniel Rockmore*2017 · 77 citations*](https://md.research.elamur.ai/free/en/papers/carlson-2017-evaluating-prose-style-transfer-bible/)
60. [**Deciphering Undersegmented Ancient Scripts Using Phonetic Prior**Jiaming Luo, Frederik Hartmann, Enrico Santus, et al.*2021 · 29 citations*](https://md.research.elamur.ai/free/en/papers/luo-2021-deciphering-undersegmented-ancient-scripts-phonetic/)
61. [**Unsupervised Pidgin Text Generation By Pivoting English Data and Self-Training**Ernie Chang, David Ifeoluwa Adelani, Xiaoyu Shen, et al.*2020 · 26 citations*](https://md.research.elamur.ai/free/en/papers/chang-2020-unsupervised-pidgin-text-generation-pivoting/)
62. [**Reinforced Rewards Framework for Text Style Transfer**Abhilasha Sancheti, Kundan Krishna, Balaji Vasan Srinivasan, et al.*2020 · 16 citations*](https://md.research.elamur.ai/free/en/papers/sancheti-2020-reinforced-rewards-framework-text-style/)
63. [**T-STAR: Truthful Style Transfer using AMR Graph as Intermediate Representation**Anubhav Jangra, Preksha Nema, Aravindan Raghuveer*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/jangra-2022-t-star-truthful-style-transfer/)

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