🧑‍🔬 Pouya Pezeshkpour

🏛️ Affiliations

🎓University of California, IrvineIrvine · United States2017–2026 · 19 paperscurrent🎓Sharif University of TechnologyTehran · Iran2014–2015 · 3 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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Large Language Models Sensitivity to The Order of Options in Multiple-Choice Questions (2023 · 261 citations)
   This paper asks how much the order of answer options affects large language models on multiple-choice questions (MCQ).
2. ParsiNLU: A Suite of Language Understanding Challenges for Persian (2021 · 65 citations)
   Persian is spoken by tens of millions of people, yet it has had very few benchmarks for high-level language understanding.
3. Measuring and Modifying Factual Knowledge in Large Language Models (2023 · 30 citations)
   Fact probing of LLMs usually checks how highly the correct answer ranks in fill-in-the-blank predictions. This treats knowledge as yes/no, depends heavily on prompt wording, and ignores most of the output distribution. Pezeshkpour proposes information-theoretic scores instead. A model is considered to know a fact if…

All works

5 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

1. Large Language Models Sensitivity to The Order of Options in Multiple-Choice QuestionsFindings of the Association for Computational LinguisticsPouya Pezeshkpour, Estevam Hruschka2023 · 261 citations
2. Embedding Multimodal Relational Data for Knowledge Base Completion ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetPouya Pezeshkpour, Liyan Chen, Sameer Singh2018 · 156 citations
3. Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications ↗Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) · no summary yetPouya Pezeshkpour, Yifan Tian, Sameer Singh2019 · 80 citations
4. ParsiNLU: A Suite of Language Understanding Challenges for PersianTransactions of the Association for Computational Linguistics (TACL)Daniel Khashabi, Arman Cohan, Siamak Shakeri, et al.2021 · 65 citations
5. Measuring and Modifying Factual Knowledge in Large Language ModelsarXiv:2306.06264Pouya Pezeshkpour2023 · 30 citations

🤝 Co-authors here

6 co-authors with a page, the most papers together first.

• Arman Cohan
• Daniel Khashabi
• Estevam Hruschka
• Faeze Brahman
• Malihe Alikhani
• Siamak Shakeri

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2023
• Transactions of the Association for Computational Linguistics (TACL): Transactions of the Association for Computational Linguistics (TACL) 2021
• Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
• Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

🔗 Cited by

Papers of our library cite their works 1,476 times (of the 149,439 papers whose bibliographies we read); 338 citing papers with a page here →.

Updated 31 October 2026

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