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Jordan Meadows

Jordan Meadows has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Code & programming languages; often with Andre Freitas, Lan Zhang, Marco Valentino.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 3 · 15 works · 18 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 18 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10565

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 ManchesterManchester · United Kingdom2021–2026 · 15 paperscurrent🔬Idiap Research InstituteMartigny-Combe · Switzerland2022–2025 · 2 papers

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).Computer Science · 2 worksArts and Humanities · 1 workArtificial Intelligence · 2 worksComputational Theory and Mathematics · 2 worksLanguage and Linguistics · 1 workInformation Systems · 1 work

🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workReasoning · 1 workCode & programming languages · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Beyond Gold Standards: Epistemic Ensemble of LLM Judges for Formal Mathematical Reasoning (2025 · 5 citations)
    Large language models can now translate natural-language mathematical statements into formal code (autoformalization), but checking whether such translations are actually correct is still difficult.
  2. FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in Lean (2026)
    Turning informal scientific derivations into machine-checkable code is difficult. Physics adds notation such as Dirac brackets and vector calculus, which Lean's Mathlib barely supports. The authors introduce FormalScience, a domain-agnostic pipeline in which LLM agents generate statements, expand proofs, and repair…

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. A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetJordan Meadows et al.2024 · 14 citations
  2. Beyond Gold Standards: Epistemic Ensemble of LLM Judges for Formal Mathematical ReasoningarXiv:2506.10903Lan Zhang, Marco Valentino, Jordan Meadows, et al.2025 · 5 citations
  3. FormalScience: Scalable Human-in-the-Loop Autoformalisation of Science with Agentic Code Generation in LeanAnnual Meeting of the Association for Computational Linguistics (ACL)Jordan Meadows, Lan Zhang, Andre Freitas2026

 Co-authors here

3 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 18 times (of the 149,439 papers whose bibliographies we read); 4 citing papers with a page here →.

Updated

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