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Ehsaneddin Asgari

Ehsaneddin Asgari has 4 papers in our library, in 2025–2026, most of them on Semitic languages, Evaluation & benchmarks, Vision & language; often with Ahlam Bashiti, Alaa Aljabari, Bilal Shalash.

4 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 17 · 129 works · 2,215 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 146 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #8784

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. 9 more institutions 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

 Papers

The most cited first (OpenAlex and our library).

  1. ImageEval 2025: The First Arabic Image Captioning Shared Task (2025 · 13 citations)
    ImageEval 2025 is the first shared task built around generating Arabic captions for images. Arabic multimodal work has been held back by a lack of native caption data, and most existing sets are translated from English, which loses cultural detail. The organizers addressed this with two linked subtasks. The first was…
  2. Fanar 2.0: Arabic Generative AI Stack (2026 · 11 citations)
    Fanar 2.0 is QCRI's second-generation Arabic-centric generative AI platform. It is built and run entirely in-house, with no external AI providers, on a modest budget of 256 H100 GPUs. Arabic is also scarce online, at roughly 0.5% of web text. Instead of scaling up, the team chose careful curation. They continued…
  3. HarfoSokhan: A Comprehensive Parallel Dataset for Transitions between Persian Colloquial and Formal Variations (2026)
    Persian has a formal written register and a colloquial one ("Shekaste-nevisi"). The two differ in vocabulary, morphology and syntax. Models built for standard Persian lose accuracy on informal social-media text, and no public large-scale parallel corpus linked the two registers. The authors address this with…
  4. QuranicMMLU: A Cognitively-Aware Benchmark for Evaluating Generative AI Solutions on Quranic Linguistic Knowledge (2026)
    QuranicMMLU is a benchmark that tests how well generative models handle the language of the Quran. Earlier Quranic and Islamic benchmarks mostly measure factual QA or retrieval, are usually multiple-choice only, and ignore cognitive difficulty.

All works

5 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. Fanar 2.0: Arabic Generative AI StackarXiv:2603.16397FANAR TEAM, Ummar Abbas, Mohammad Shahmeer Ahmad, et al.2026 · 11 citations
  2. PahGen: Generating Ancient Pahlavi Text via Grammar-guided Zero-shot Translation ↗Proceedings of the Eighth Workshop on Technologies for Machine Translation of Low-Resource Languages (LoResMT 2025) · no summary yetFarhan Farsi et al.2025 · 2 citations
  3. QuranicMMLU: A Cognitively-Aware Benchmark for Evaluating Generative AI Solutions on Quranic Linguistic KnowledgearXiv:2609.22038 · Arabic NLP 2026Rawan El Ghali; Umm Kulsoom; Anas Madkoor; Dima Faris Alsaudi; Roaa Abdelmagid; Roaa Ibrahim; Raghad Mousa; Hamza Aljaji; Abdullah Khanafer; Abdallah Alkanani; Salah Feras Alali; Rawan Khaled Mohamed;, Ehsaneddin Asgari2026

 Co-authors here

12 of 15 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 146 times (of the 149,439 papers whose bibliographies we read); 113 citing papers with a page here →.

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