2 citations · 2 across the 3 of their papers we have counts for
6 papers
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…
Transformers know more than they can tell -- Learning the Collatz sequence
François Charton, Ashvni Narayanan
We investigate transformer prediction of long Collatz steps, a complex arithmetic function that maps odd integers to their distant successors in the Collatz sequence ( $u_{n+1}=u_n…
Learning Euler Factors of Elliptic Curves
Angelica Babei, François Charton, Edgar Costa +5
We apply transformer models and feedforward neural networks to predict Frobenius traces from elliptic curves given other traces . We train further models to predict $a_p…
Formalization of -adic -functions in Lean 3
Ashvni Narayanan
The Euler--Riemann zeta function is a largely studied numbertheoretic object, and the birthplace of several conjectures, such as the Riemann Hypothesis. Different approaches are us…
Towards a Mathematics Formalisation Assistant using Large Language Models
Ayush Agrawal, Siddhartha Gadgil, Navin Goyal +2
Mathematics formalisation is the task of writing mathematics (i.e., definitions, theorem statements, proofs) in natural language, as found in books and papers, into a formal langua…
A formalization of Dedekind domains and class groups of global fields
Anne Baanen, Sander R. Dahmen, Ashvni Narayanan +1
Dedekind domains and their class groups are notions in commutative algebra that are essential in algebraic number theory. We formalized these structures and several fundamental pro…