--- title: "Jason Rute — author profile and papers — Elamur Research" description: "Jason Rute, IBM: 2 papers on Elamur Research (2021–2024), h-index 8 — affiliations, topics, co-authors and who cites them in our library." canonical: "https://research.elamur.ai/free/en/authors/jason-rute/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jason-rute/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Jason Rute # Jason Rute Jason Rute has 2 papers in our library, in 2021–2024, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Edward W. Ayers](https://md.research.elamur.ai/free/en/authors/edward-w-ayers/), [Jesse Michael Han](https://md.research.elamur.ai/free/en/authors/jesse-michael-han/), [Miroslav Olšák](https://md.research.elamur.ai/free/en/authors/miroslav-olsak/). 2 papers in our library · 2021–2024 [OpenAlex](https://openalex.org/A5054310314) · [ORCID](https://orcid.org/0000-0002-6247-1882) · [**h-index 8**](https://openalex.org/authors/A5054310314) · [27 works](https://openalex.org/works?filter=author.id:A5054310314) · [529 citations](https://openalex.org/works?filter=author.id:A5054310314&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/jason-rute/#papers) · [🔗 Cited 121 times in our library](https://md.research.elamur.ai/free/en/authors/jason-rute/cited-by/) · [⭐ Paper Stars ranking: #8382](https://md.research.elamur.ai/free/en/paper-stars/page/84/#star-8382) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Jason+Rute) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Jason+Rute) · [dblp](https://dblp.org/search?q=Jason+Rute) · [ACL Anthology](https://aclanthology.org/search/?q=Jason+Rute) ## Affiliations [🏢**IBM** Armonk · United States 2021–2024 · 3 papers*current*](https://md.research.elamur.ai/free/en/companies/ibm/) · [🎓**Pennsylvania State University** State College · United States 2014–2021 · 9 papers](https://md.research.elamur.ai/free/en/universities/pennsylvania-state-university/) · [🎓**Carnegie Mellon University** Pittsburgh · United States 2012–2013 · 2 papers](https://md.research.elamur.ai/free/en/universities/carnegie-mellon-university/) 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 3 The field of science this work belongs to (OpenAlex fields).[Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Computational Theory and Mathematics · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computational-theory-and-mathematics/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) ## Works by year ### 2020s [**2024** 1 paper](https://md.research.elamur.ai/free/en/authors/jason-rute/year/2024/) · [**2021** 1 paper](https://md.research.elamur.ai/free/en/authors/jason-rute/year/2021/) ## Papers The most cited first (OpenAlex and our library). 1. **[Proof Artifact Co-training for Theorem Proving with Language Models](https://md.research.elamur.ai/free/en/papers/han-2021-proof-artifact-co-training-theorem/)** *(2021 · 82 citations)* Neural theorem provers for big formal libraries don't have much training data. Human-written proofs take a lot of work to produce, so large Transformer models overfit fast and stop improving as they get bigger. The authors propose PACT (Proof Artifact Co-Training) to get more data. Lean's kernel stores every proof as… 2. **[Graph2Tac: Online Representation Learning of Formal Math Concepts](https://md.research.elamur.ai/free/en/papers/blaauwbroek-2024-graph2tac-online-representation-learning-formal/)** *(2024 · 19 citations)* The paper tackles a practical gap in machine-learning provers for Coq: models trained offline cannot easily handle the new definitions, lemmas and proofs that appear when working in an unfamiliar formalization project. ## Co-authors here 5 co-authors with a page, the most papers together first. - [Edward W. Ayers](https://md.research.elamur.ai/free/en/authors/edward-w-ayers/) - [Jesse Michael Han](https://md.research.elamur.ai/free/en/authors/jesse-michael-han/) - [Miroslav Olšák](https://md.research.elamur.ai/free/en/authors/miroslav-olsak/) - [Stanislas Polu](https://md.research.elamur.ai/free/en/authors/stanislas-polu/) - [Yuhuai Wu](https://md.research.elamur.ai/free/en/authors/yuhuai-wu/) ## Cited by Papers of our library cite their works 121 times (of the 149,439 papers whose bibliographies we read); [73 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/jason-rute/cited-by/). Updated 3 November 2026