Marzieh Fadaee
Marzieh Fadaee has 4 papers in our library, in 2017–2025, most of them on Multilingual & cross-lingual NLP, Bias, fairness & safety, Machine translation; often with Beyza Ermis, Julia Kreutzer, Sara Hooker.
OpenAlex · ORCID · Wikidata · h-index 11 · 62 works · 494 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 1,562 times in our library · 5 more in our library without a page yet · ⭐ Paper Stars ranking: #3738
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 worksSafety Research · 2 worksSocial Sciences · 2 works
🧭 Topics 5Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 3 worksLow-resource languages · 1 workMachine translation · 1 workBias, fairness & safety · 2 worksLanguage models & pretraining · 1 work
Works by year
2020s
2010s
Papers
- Data Augmentation for Low-Resource Neural Machine Translation (2017 · 425 citations)
Neural machine translation needs large parallel corpora. When data are scarce, words that appear only a few times end up with poorly learned representations. Borrowing the idea of data augmentation from computer vision, the authors introduce translation data augmentation (TDA), which builds extra training pairs by… - The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm (2024 · 49 citations)
Most LLM safety alignment targets English and relies on Western-centric data. This leaves non-English users more exposed and lets other languages serve as a route around guardrails. The paper asks three things: whether harm mitigation can work across many languages at once, whether it transfers across languages, and… - M-RewardBench: Evaluating Reward Models in Multilingual Settings (2025 · 28 citations)
Reward models (RMs) steer LLM alignment, but they are built and tested almost entirely in English. This paper asks how well RMs judge responses in other languages. The authors built M-RewardBench, a benchmark of about 2.87k preference instances spanning 23 typologically varied languages, including Ukrainian. - The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It (2025 · 25 citations)
This survey examines how much LLM safety research covers languages other than English. The authors reviewed nearly 300 papers from 2020–2024 published at ∗ACL conferences and workshops. They found candidate papers by searching abstracts for "safe" and "safety". They then labeled each paper by hand with a safety…
All works
- Data Augmentation for Low-Resource Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Marzieh Fadaee, Arianna Bisazza, Christof Monz2017 · 425 citations
- Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetArash Ahmadian et al.2024 · 217 citations
- Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetMarzieh Fadaee, Christof Monz2018 · 122 citations
- InPars: Data Augmentation for Information Retrieval using Large Language Models ↗arXiv:2202.05144 · no summary yetLuiz Bonifacio et al.2022 · 72 citations
- The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce HarmConference on Empirical Methods in Natural Language Processing (EMNLP)Aakanksha, Arash Ahmadian, Beyza Ermis, et al.2024 · 49 citations
- M-RewardBench: Evaluating Reward Models in Multilingual SettingsAnnual Meeting of the Association for Computational Linguistics (ACL)Srishti Gureja, Lester James V. Miranda, Shayekh Bin Islam, et al.2025 · 28 citations
- The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating ItConference on Empirical Methods in Natural Language Processing (EMNLP)Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.2025 · 25 citations
- The Leaderboard Illusion ↗arXiv:2504.20879 · no summary yetShivalika Singh et al.2025 · 22 citations
- Déj\‘a Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation ↗arXiv:2504.11829 · no summary yetJulia Kreutzer et al.2025 · 7 citations
Co-authors here
- Beyza Ermis ×2
- Julia Kreutzer ×2
- Sara Hooker ×2
- Arash Ahmadian
- Arianna Bisazza
- Christof Monz
- Lester James V. Miranda
- Nathan Lambert
- Rishabh Maheshwary
- Sebastian Ruder
- Seraphina Goldfarb-Tarrant
- Stephen H. Bach
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×5: ACL 2025, ACL 2017
- Conference on Empirical Methods in Natural Language Processing (EMNLP) ×3: EMNLP 2025, EMNLP 2024
Cited by
Updated
This page in Markdown → https://md.research.elamur.ai/free/en/authors/marzieh-fadaee/