Amr Mohamed
Amr Mohamed has 5 papers in our library, in 2025–2026, most of them on Language models & pretraining, Semitic languages, Low-resource languages; often with Guokan Shang, Michalis Vazirgiannis, Hadi Abdine.
OpenAlex · ORCID · Wikidata · h-index 43 · 428 works · 9,652 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 37 times in our library · ⭐ Paper Stars ranking: #8088
Affiliations
Fields, topics and concepts
📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 5 worksArts and Humanities · 5 worksComputer Science · 5 worksLanguage and Linguistics · 5 works
🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 5 worksSemitic languages · 2 worksLow-resource languages · 1 work
Works by year
2020s
Papers
- Atlas-Chat: Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect (2025 · 18 citations)
Arabic-focused LLMs such as Jais, AceGPT and ALLaM mostly balance English and Modern Standard Arabic and largely ignore spoken dialects. - Nile-Chat: Egyptian Language Models for Arabic and Latin Scripts (2025 · 9 citations)
Egyptian Arabic is often written in two ways: in Arabic script and in a Latin-based romanization called Arabizi or Franco-Arabic. - Beyond Random Sampling: Efficient Language Model Pretraining via Curriculum Learning (2026 · 7 citations)
Large language models are usually pretrained on documents fed in random order. This leaves open whether arranging data from simple to complex could save compute. The authors run what they present as the first systematic, large-scale test of curriculum learning for LLM pretraining. They use an English subset of… - Lost in the Mix: Evaluating LLM Understanding of Code-Switched Text (2026 · 6 citations)
The paper asks whether large language models still comprehend and reason well when a text mixes languages (code-switching, CSW). - Fast-Decoding Diffusion Language Models via Progress-Aware Confidence Schedules (2026)
Diffusion large language models (dLLMs) can generate text in parallel and attend in both directions, but they are slow at inference.
Co-authors here
- Guokan Shang ×5
- Michalis Vazirgiannis ×5
- Hadi Abdine ×3
- Yang Zhang ×3
- Eric P. Xing ×2
- Preslav Nakov ×2
- Mohamed Anwar
- Omar El Herraoui
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Arabic Natural Language Processing Conference (ArabicNLP): ArabicNLP 2025
- Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Workshop on Language Models for Low-Resource Languages: Workshop on Language Models for Low-Resource Languages 2025
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