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Farah Adeeba

Farah Adeeba has 2 papers in our library, in 2026, most of them on Language models & pretraining, Evaluation & benchmarks, Semitic languages; often with Hassan Sajjad, Ahmed Abdelali, Brian Dillon.

2 papers in our library · 2026

OpenAlex · ORCID · h-index 7 · 30 works · 131 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 12 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9692

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

🎓University of KonstanzKonstanz · Germany2014–2026 · 11 paperscurrent🎓University of Massachusetts AmherstAmherst Center · United States2026 · 2 paperscurrent🎓University of Engineering and Technology LahoreLahore · Pakistan2014–2025 · 9 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.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Semitic languages · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. AbjadGenEval: Abjad AI Generated Text Detection Shared Task for Languages Using Arabic Script at AbjadNLP 2026 (2026 · 10 citations)
    AbjadGenEval is a shared task held at the AbjadNLP workshop (EACL 2026). It tests whether systems can tell human-written news from LLM-generated news in languages written in Arabic script. The organizers argue that existing detectors were built mostly for English and break down on Arabic-script text, where rich…
  2. UrBLiMP: A Benchmark for Evaluating the Linguistic Competence of Large Language Models in Urdu (2026 · 2 citations)
    The authors built a diagnostic benchmark that tests how well large language models have acquired Urdu grammar.

All works

3 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. AbjadGenEval: Abjad AI Generated Text Detection Shared Task for Languages Using Arabic Script at AbjadNLP 2026Workshop on NLP for Languages Using Arabic ScriptSaad Ezzini, Irfan Ahmad, Salmane Chafik, et al.2026 · 10 citations
  2. UrBLiMP: A Benchmark for Evaluating the Linguistic Competence of Large Language Models in UrduFindings of the Association for Computational LinguisticsFarah Adeeba, Brian Dillon, Hassan Sajjad, et al.2026 · 2 citations
  3. AbjadStyleTransfer: Authorship Style Transfer for Arabic-Script Languages at AbjadNLP 2026 ↗Proceedings of the 2nd Workshop on NLP for Languages Using Arabic Script · no summary yetShadi Abudalfa et al.2026 · 1 citation

 Co-authors here

11 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 12 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/farah-adeeba/