Abstract Language models have achieved remarkable performance on a wide range of
tasks that require natural language understanding. Nevertheless, state-of-the-art models …

Automated theorem provers and formal proof assistants are general reasoning systems that
are in theory capable of proving arbitrarily hard theorems, thus solving arbitrary problems …

In this work we extend an instantiation-based theorem prover iProver with machine learning
(ML) guidance based on graph neural networks. For this we implement an interactive mode …

We significantly improve the performance of the E automated theorem prover on the Isabelle
Sledgehammer problems by combining learning and theorem proving in several ways. In …

As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically
proves about 60\% of the Mizar theorems in the hammer setting. We also automatically …

he cvc5 solver is today one of the strongest systems for solving first order problems with
theories but also without them. In this work we equip its enumeration-based instantiation …

Premise selection is crucial for large theory reasoning with automated theorem provers as
the sheer size of the problems quickly leads to resource exhaustion. This paper proposes a …

In this work we considerably improve the state-of-the-art SMT solving on first-order
quantified problems by efficient machine learning guidance of quantifier selection …

In this work, we prove over 3000 previously ATP-unproved Mizar/MPTP problems by using
several ATP and AI methods, raising the number of ATP-solved Mizar problems from 75% to …

With artificial intelligence (AI) being well established within the daily lives of research
communities, we turn our gaze toward an application area that appears intuitively unsuited …