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Mahmoud Khademi

Mahmoud Khademi has 2 papers in our library, in 2017–2025, most of them on Language models & pretraining, Reasoning; often with Dongdong Zhang, Furu Wei, Hany Awadalla.

2 papers in our library · 2017–2025

OpenAlex · ORCID · Wikidata · h-index 12 · 42 works · 542 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 270 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #7111

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

🎓Queen's UniversityKingston · Canada2015–2026 · 2 papersEducation since 2015 · PhD, Chemical EngineeringEmployment · Senior Research Engineer, Department of Chemical Engineeringcurrent🏢MicrosoftRedmond · United States2023–2025 · 9 papers🎓Simon Fraser UniversityBurnaby · Canada2017–2020 · 5 papers🎓Sharif University of TechnologyTehran · Iran2008–2013 · 4 papers🎓McMaster UniversityHamilton · Canada2014–2015 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 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).Computer Science · 2 worksComputer Science Applications · 1 workInformation Systems · 1 workSoftware · 1 workArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20251 paper

2010s

20171 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Learning to Represent Programs with Graphs (2017 · 127 citations)
    The authors argue that most neural networks for code analysis treat code like ordinary text, either as a sequence of tokens or as a syntax tree.
  2. Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective (2025 · 23 citations)
    Current LLM math solvers are usually tuned for a single reasoning style. Some use natural-language chains of thought, others use executable code, and others use formal proofs. As a result, a model strong at arithmetic word problems often fails at theorem proving, and the reverse. The authors propose…

All works

4 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. Learning to Represent Programs with GraphsarXiv:1711.00740Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi2017 · 127 citations
  2. Towards a clinically accessible radiology foundation model: open-access and lightweight, with automated evaluation ↗arXiv:2403.08002 · Nature Communications volume 16, Article number: 3108 (2025) · no summary yetJuan Manuel Zambrano Chaves et al.2024 · 57 citations
  3. CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetZineng Tang et al.2024 · 34 citations
  4. Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Yiyao Yu, Yuxiang Zhang, Dongdong Zhang, et al.2025 · 23 citations

 Co-authors here

12 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 270 times (of the 149,439 papers whose bibliographies we read); 71 citing papers with a page here →.

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