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Sheza Munir

Sheza Munir has 2 papers in our library, in 2025, most of them on Language models & pretraining, Evaluation & benchmarks; often with Lechen Zhang, Lu Wang, Farima Fatahi Bayat.

2 papers in our library · 2025

OpenAlex · ORCID · h-index 2 · 13 works · 12 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 22 times in our library · ⭐ Paper Stars ranking: #8644

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 MichiganAnn Arbor · United States2024–2026 · 7 paperscurrent🎓University of TorontoToronto · Canada2026 · 4 paperscurrent

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 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workSocial Sciences · 1 workSociology and Political Science · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20252 papers

 Papers

The most cited first (OpenAlex and our library).

  1. FactBench: A Dynamic Benchmark for In-the-Wild Language Model Factuality Evaluation (2025 · 16 citations)
    Existing long-form factuality benchmarks are fixed snapshots, which exposes them to data contamination. They also cover narrow scenarios, such as biographies or LM-written questions, rather than what real users ask. The authors address this by mining in-the-wild prompts from LMSYS-Chat-1M. They cluster the prompts…
  2. VeriFact: Enhancing Long-Form Factuality Evaluation with Refined Fact Extraction and Reference Facts (2025 · 11 citations)
    Judging whether long LLM answers are factually correct is hard because individual claims often depend on context spread across several sentences.

 Co-authors here

5 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 22 times (of the 149,439 papers whose bibliographies we read); 7 citing papers with a page here →.

Updated

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