---
title: "Who cites On Adversarial Examples for — 71 citing papers"
description: "71 papers of the Elamur Research library cite «On Adversarial Examples for Character-Level Neural Machine Translation», found in their…"
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---
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# Who cites «On Adversarial Examples for Character-Level Neural Machine Translation»

71 papers of our library cite it (of the 141,840 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «On Adversarial Examples for Character-Level Neural Machine Translation»](https://md.research.elamur.ai/free/en/papers/ebrahimi-2018-adversarial-examples-character-level-neural/)

1. **[Analysis Methods in Neural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/belinkov-2019-analysis-methods-neural-language-processing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yonatan Belinkov, James Glass*2019 · 737 citations*
2. **[Weight Poisoning Attacks on Pretrained Models](https://md.research.elamur.ai/free/en/papers/kurita-2020-weight-poisoning-attacks-pretrained-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Keita Kurita, Paul Michel, Graham Neubig*2020 · 415 citations*
3. **[Combating Adversarial Misspellings with Robust Word Recognition](https://md.research.elamur.ai/free/en/papers/pruthi-2019-combating-adversarial-misspellings-robust-word/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danish Pruthi, Bhuwan Dhingra, Zachary C. Lipton*2019 · 389 citations*
4. **[Robust Neural Machine Translation with Doubly Adversarial Inputs](https://md.research.elamur.ai/free/en/papers/cheng-2019-robust-neural-machine-translation-doubly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yong Cheng, Lu Jiang, Wolfgang Macherey*2019 · 324 citations*
5. [**Scaling Laws for Reward Model Overoptimization arXiv:2210.10760**Leo Gao, John Schulman, Jacob Hilton*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-scaling-laws-reward-model-overoptimization/)
6. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 253 citations*
7. **[On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models](https://md.research.elamur.ai/free/en/papers/michel-2019-evaluation-adversarial-perturbations-sequence-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Paul Michel, Xian Li, Graham Neubig, et al.*2019 · 162 citations*
8. **[Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/belinkov-2019-don-t-take-premise-granted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yonatan Belinkov, Adam Poliak, Stuart Shieber, et al.*2019 · 121 citations*

63 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/ebrahimi-2018-adversarial-examples-character-level-neural/) — On Adversarial Examples for Character-Level Neural Machine Translation