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Miles Cranmer

Miles Cranmer has 3 papers in our library, in 2020–2024, most of them on Language models & pretraining, Tokenization & segmentation; often with Alberto Bietti, Alvaro Sanchez-Gonzalez, Atharva Sehgal.

3 papers in our library · 2020–2024

OpenAlex · ORCID · Wikidata · h-index 18 · 78 works · 1,570 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 69 times in our library · 8 more in our library without a page yet · ⭐ Paper Stars ranking: #5603

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 CambridgeCambridge · United Kingdom2023–2026 · 15 papersEmployment since 2023 · Assistant Professor, Department of Applied Mathematics and Theoretical Physics; Institute of Astronomycurrent🎓Princeton UniversityPrinceton · United States2018–2024 · 32 papersEducation 2018–2023 · PhD, Astrophysical SciencesEducation 2018–2020 · MA, Astrophysical SciencesEmployment 2018–2023 · Graduate Student, Astrophysical Sciences🔬Flatiron InstituteNew York · United States2022–2024 · 7 papersEmployment 2023 · Research Fellow, Center for Computational Astrophysics🎓McGill UniversityMontreal · Canada2014–2018 · 2 papersEducation 2014–2018 · B.Sc., Physics🔬Trottier Space Institute at McGillMontreal · Canada2017–2018 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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.

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksMaterials Chemistry · 1 workMaterials Science · 1 workPhysics and Astronomy · 1 workStatistical and Nonlinear Physics · 1 workArts and Humanities · 1 workComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 work

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

 Works by year

2020s

20241 paper20231 paper20201 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Discovering Symbolic Models from Deep Learning with Inductive Biases (2020 · 272 citations)
    Symbolic regression produces compact, interpretable formulas, but its search cost grows exponentially with the number of inputs.
  2. Symbolic Regression with a Learned Concept Library (2024 · 23 citations)
    Symbolic regression (SR) looks for short mathematical expressions that explain a dataset. Its search space is discrete and grows exponentially, and leading genetic methods such as PySR explore it through random mutation and crossover. The authors propose LaSR, which adds a human-like layer of abstraction. An LLM…
  3. xVal: A Continuous Numerical Tokenization for Scientific Language Models (2023 · 19 citations)
    Standard LLMs split numbers into discrete text tokens, so they do not capture magnitude or continuity well.

All works

11 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. Discovering Symbolic Models from Deep Learning with Inductive BiasesarXiv:2006.11287Miles Cranmer, Alvaro Sanchez-Gonzalez, Peter Battaglia, et al.2020 · 272 citations
  2. AstroCLIP: a cross-modal foundation model for galaxies ↗Monthly Notices of the Royal Astronomical Society · no summary yetLiam Parker et al.2024 · 76 citations
  3. Symbolic Regression with a Learned Concept LibraryConference on Neural Information Processing Systems (NeurIPS)Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.2024 · 23 citations
  4. Multiple Physics Pretraining for Physical Surrogate Models ↗arXiv (Cornell University) · no summary yetMcCabe, Michael et al.2023 · 22 citations
  5. xVal: A Continuous Numerical Tokenization for Scientific Language ModelsarXiv:2310.02989Siavash Golkar, Mariel Pettee, Michael Eickenberg, et al.2023 · 19 citations
  6. Multiple Physics Pretraining for Spatiotemporal Surrogate Models ↗neural information processing systems · no summary yetMichael McCabe et al.2024 · 14 citations
  7. AION-1: Omnimodal Foundation Model for Astronomical Sciences ↗neural information processing systems · no summary yetLiam Parker et al.2025 · 2 citations
  8. Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task ↗arXiv (Cornell University) · no summary yetSiavash Golkar et al.2024 · 2 citations
  9. MIMIC: A Generative Multimodal Foundation Model for Biomolecules ↗arXiv (Cornell University) · no summary yetSiavash Golkar et al.2026 · 1 citation
  10. Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence ↗arXiv (Cornell University) · no summary yetPayel Mukhopadhyay et al.2026
  11. Universal Spectral Tokenization via Self-Supervised Panchromatic Representation Learning ↗arXiv (Cornell University) · no summary yetJeff Shen et al.2025

 Co-authors here

7 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 69 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

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