3 papers
cs.LG2026
Discovering New Theorems via LLMs with In-Context Proof Learning in Lean
Kazumi Kasaura, Naoto Onda, Yuta Oriike +3
Large Language Models (LLMs) have demonstrated significant promise in formal theorem proving. In this study, we investigate the ability of LLMs to discover novel theorems and produ…
cs.LG2026
Lean Formalization of Generalization Error Bound by Rademacher Complexity and Dudley's Entropy Integral
Sho Sonoda, Kazumi Kasaura, Yuma Mizuno +2
Understanding and certifying the generalization performance of machine learning algorithms -- i.e. obtaining theoretical estimates of the test error from the training error -- is a…
cs.AI2025
LeanConjecturer: Automatic Generation of Mathematical Conjectures for Theorem Proving
Naoto Onda, Kazumi Kasaura, Yuta Oriike +3
We introduce LeanConjecturer, a pipeline for automatically generating university-level mathematical conjectures in Lean 4 using Large Language Models (LLMs). Our hybrid approach co…