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Hussein Mozannar

Hussein Mozannar has 2 papers in our library, in 2019–2025, most of them on Language models & pretraining, Question answering, Evaluation & benchmarks; often with Eric Horvitz, Gagan Bansal, Hazem Hajj.

2 papers in our library · 2019–2025

OpenAlex · ORCID · Wikidata · h-index 9 · 37 works · 443 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 118 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #5467

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

🏢MicrosoftRedmond · United States2024–2026 · 6 paperscurrent🎓Massachusetts Institute of TechnologyCambridge · United States2020–2024 · 10 papersEmployment🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2023–2024 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 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.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work

🧭 Topics 4Research subjects and languages the work is about.Question answering · 1 workSemitic languages · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Neural Arabic Question Answering (2019 · 206 citations)
    Arabic question answering has trailed English, mainly because there were no sizeable span-annotated datasets. Earlier Arabic systems mostly used classical retrieval and were tested on very small question sets. The authors target open-domain factual QA, where every answer must be a text span from Arabic Wikipedia.
  2. Navigating Rifts in Human-LLM Grounding: Study and Benchmark (2025 · 19 citations)
    Conversational LLMs are tuned mainly to execute instructions. They rarely do the joint work people use to build shared understanding, such as checking assumptions, asking what was meant, or proposing next steps. The authors studied this gap using logs from three sources: WildChat, Bing Chat, and the Wizard-of-Oz…

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. Neural Arabic Question AnsweringArabic Natural Language Processing Workshop (WANLP)Hussein Mozannar, Elie Maamary, Karl El Hajal, et al.2019 · 206 citations
  2. Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks ↗arXiv:2411.04468 · no summary yetAdam Fourney et al.2024 · 54 citations
  3. Navigating Rifts in Human-LLM Grounding: Study and BenchmarkAnnual Meeting of the Association for Computational Linguistics (ACL)Omar Shaikh, Hussein Mozannar, Gagan Bansal, et al.2025 · 19 citations

 Co-authors here

4 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 118 times (of the 149,439 papers whose bibliographies we read); 60 citing papers with a page here →.

Updated

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