🧑‍🔬 Rafael Mosquera

🏛️ Affiliations

🎓Alexandria UniversityAlexandria · Egypt2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models (2024 · 133 citations)
   LLM alignment depends on human feedback, yet most existing preference datasets offer only binary comparisons, draw on narrow crowdworker pools and record little about who the raters are.
2. CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data (2026 · 3 citations)
   Language identification (LID) is often treated as a solved task. In practice, it remains unreliable for many languages on noisy, mixed web text, which is the main source of multilingual pre-training corpora. Most existing benchmarks, such as FLORES, UDHR and Bible data, are clean, translated or religious, so they…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora ↗Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning · no summary yetAlex Warstadt et al.2023 · 232 citations
2. The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.2024 · 133 citations
3. The ML-SUPERB 2.0 Challenge: Towards Inclusive ASR Benchmarking for All Language Varieties ↗Interspeech (USB) · no summary yetWilliam C. Chen et al.2025 · 4 citations
4. CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web DataAnnual Meeting of the Association for Computational Linguistics (ACL)Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett, et al.2026 · 3 citations
5. Overview of the Shared Task on Machine Translation Gender Bias Evaluation with Multilingual Holistic Bias ↗Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP) · no summary yetMarta R. Costa-jussà et al.2024 · 1 citation

🤝 Co-authors here

12 of 16 co-authors with a page, the most papers together first.

• Adina Williams
• Atnafu Lambebo Tonja
• Bertie Vidgen
• Catherine Arnett
• Hannah Rose Kirk
• He He
• Idris Abdulmumin
• Katerina Margatina
• Laurie Burchell
• Malte Ostendorff
• Max Bartolo
• Paul Rottger

Venues

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

• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2024
• Interspeech (USB)
• Proceedings of the 5th Workshop on Gender Bias in Natural Language Processing (GeBNLP)
• Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning

🔗 Cited by

Papers of our library cite their works 281 times (of the 149,439 papers whose bibliographies we read); 77 citing papers with a page here →.

Updated 2 November 2026

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