works on

From the 2 of 6 linked papers with an AI index.

most citedOn Conservative Matrix Fields: Continuous Asymptotics and Arithmetic

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

physics.hist-ph2026

Can AI Follow In Einstein's Footsteps?

Michael Shalyt, Nathan Regev, Marin Soljačić +1

The paper surveys how AI has helped physics discovery, noting a shift from early equation‑finding methods to modern high‑accuracy predictors, and argues that AI still lacks the abi…

math.NT20261 cited

On Conservative Matrix Fields: Continuous Asymptotics and Arithmetic

Shachar Weinbaum, Elyasheev Leibtag, Rotem Kalisch +2

The paper introduces Conservative Matrix Fields as a framework for analyzing D‑finite functions and uses them to derive asymptotic properties of linear forms in periods, such as mu…

math.HO2026

The Ramanujan Challenge For AI

Michael Shalyt, Rotem Kalisch, Carsten Schneider +7

To help evaluate the mathematical skills of current AI systems, we present a set of formulas for fundamental mathematical constants. These problems are attractive for AI evaluation…

cs.CL2026

ASyMOB: Algebraic Symbolic Mathematical Operations Benchmark

Michael Shalyt, Rotem Elimelech, Ido Kaminer

Large language models (LLMs) are increasingly applied to symbolic mathematics, yet existing evaluations often conflate pattern memorization with genuine reasoning. To address this…

math.HO2026

From Euler to AI: Unifying Formulas for Mathematical Constants

Tomer Raz, Michael Shalyt, Elyasheev Leibtag +4

The constant has fascinated scholars throughout the centuries, inspiring numerous formulas for its evaluation, such as infinite sums and continued fractions. Despite their ind…

cs.AI2024

Unsupervised Discovery of Formulas for Mathematical Constants

Michael Shalyt, Uri Seligmann, Itay Beit Halachmi +3

Ongoing efforts that span over decades show a rise of AI methods for accelerating scientific discovery, yet accelerating discovery in mathematics remains a persistent challenge for…