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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.

4 papers in our library · 2017–2025

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

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. 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…
  2. 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…
  3. 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.
  4. 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

9 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. 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
  2. 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
  3. InPars: Data Augmentation for Information Retrieval using Large Language Models ↗arXiv:2202.05144 · no summary yetLuiz Bonifacio et al.2022 · 72 citations
  4. The Leaderboard Illusion ↗arXiv:2504.20879 · no summary yetShivalika Singh et al.2025 · 22 citations
  5. 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

12 of 13 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 1,562 times (of the 149,439 papers whose bibliographies we read); 311 citing papers with a page here →.

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