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Fateme Hashemi Chaleshtori

Fateme Hashemi Chaleshtori has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning; often with Ana Marasovic, Nathan Stringham, Yonatan Belinkov.

2 papers in our library · 2025–2026

OpenAlex · ORCID · Wikidata · h-index 4 · 11 works · 24 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 15 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9455

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 UtahSalt Lake City · United States2022–2026 · 3 papersEducation since 2022 · Ph.D., School of Computingcurrent🎓Colorado State UniversityFort Collins · United States2019–2023 · 3 papersEducation 2019–2022 · M.S., Computer Science🎓Amirkabir University of TechnologyTehran · Iran2014–2019Education 2014–2019 · B.Sc., Computer Engineering and Information Technology

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 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 workSafety Research · 1 workSocial Sciences · 1 work

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

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps (2025 · 15 citations)
    The paper asks whether the step-by-step reasoning (chain of thought, CoT) that language models produce reflects the knowledge the model actually relies on.
  2. Teaching People LLM's Errors and Getting it Right (2026)
    Users often trust LLMs on tasks the models handle poorly. An earlier approach, the AI-integration teaching pipeline of Mozannar et al. (2023), tried to fix this. It finds regions where a model tends to fail, describes them in natural language and teaches users to avoid the model there. However, it gave no gains for…

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. Measuring Chain of Thought Faithfulness by Unlearning Reasoning StepsConference on Empirical Methods in Natural Language Processing (EMNLP)Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.2025 · 15 citations
  2. BriefMe: A Legal NLP Benchmark for Assisting with Legal Briefs ↗Findings of the Association for Computational Linguistics: ACL 2025 · no summary yetJesse Woo et al.2025 · 9 citations
  3. Teaching People LLM's Errors and Getting it RightWorkshop on Trustworthy NLPNathan Stringham, Fateme Hashemi Chaleshtori, Xinyuan Yan, et al.2026

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

Updated

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