During 2026–27, the CMSA will host a seminar on New Technologies in Mathematics, organized by Michael Douglas and Luca Pesce. This seminar will take place on Wednesdays from 2:00 pm–3:00 pm (Eastern Time). The meetings will take place in Room G10 at the CMSA, 20 Garden Street, Cambridge MA 02138, and some meetings will take place virtually on Zoom or be held in hybrid formats. To learn how to attend,  join the seminar mailing list or contact Michael Douglas (mdouglas@cmsa.fas.harvard.edu).

The schedule will be updated as talks are confirmed.

Seminar videos can be found at the CMSA Youtube site: New Technologies in Mathematics Playlist

  • Transformers for maths, and maths for transformers

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/Sc6k06wVX3s New Technologies in Mathematics Seminar Speaker: François Charton, Meta AI Title:  Transformers for maths, and maths for transformers Abstract: Transformers can be trained to solve problems of mathematics. I present […]

  • LeanDojo: Theorem Proving with Retrieval-Augmented Language Models

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/u-pkmdkQoMU New Technologies in Mathematics Seminar Speaker: Alex Gu, MIT Dept. of EE&CS Title: LeanDojo: Theorem Proving with Retrieval-Augmented Language Models Abstract: Large language models (LLMs) have shown promise in proving formal […]

  • Physics of Language Models: Knowledge Storage, Extraction, and Manipulation

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/M25cbX5do8Y New Technologies in Mathematics Seminar Speaker: Yuanzhi Li, CMU Dept. of Machine Learning and Microsoft Research Title: Physics of Language Models: Knowledge Storage, Extraction, and Manipulation Abstract: Large language models (LLMs) can […]

  • Llemma: an open language model for mathematics

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/bRHb-MVExJ4 New Technologies in Mathematics Seminar Speaker: Sean Welleck, CMU, Language Technologies Institute Title: Llemma: an open language model for mathematics Abstract: We present Llemma: 7 billion and 34 billion […]

  • Peano: Learning Formal Mathematical Reasoning Without Human Data

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/a2S_-pl6onM New Technologies in Mathematics Seminar Speaker: Gabriel Poesia, Dept. of Computer Science, Stanford University Title: Peano: Learning Formal Mathematical Reasoning Without Human Data Abstract: Peano is a theorem proving […]

  • On the Power of Forward pass through Transformer Architectures

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/JYt-ldZ3DqM New Technologies in Mathematics Seminar Speaker: Abhishek Panigrahi, Dept. of Computer Science, Princeton University Title: On the Power of Forward pass through Transformer Architectures Abstract: Highly trained transformers are […]

  • Approaches to the formalization of differential geometry

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/oiOpudgC0J4 New Technologies in Mathematics Seminar Speaker: Heather Macbeth, Fordham University Title: Approaches to the formalization of differential geometry Abstract: In the last five years, there has been early work […]

  • What Algorithms can Transformers Learn? A Study in Length Generalization

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    New Technologies in Mathematics Seminar Speaker: Preetum Nakkiran, Apple Title: What Algorithms can Transformers Learn? A Study in Length Generalization Abstract: Large language models exhibit many surprising “out-of-distribution” generalization abilities, […]

  • LILO: Learning Interpretable Libraries by Compressing and Documenting Code

    CMSA Room G10 CMSA, 20 Garden Street, Cambridge, MA, United States

    https://youtu.be/ZDMRN0Iyp28 New Technologies in Mathematics Seminar Speaker: Gabe Grand, MIT CSAIL and Dept. of EE&CS Title: LILO: Learning Interpretable Libraries by Compressing and Documenting Code Abstract: While large language models (LLMs) […]