10 citations · 26 across the 16 of their papers we have counts for
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cs.AI2024
CON-FOLD -- Explainable Machine Learning with Confidence
Lachlan McGinness, Peter Baumgartner
FOLD-RM is an explainable machine learning classification algorithm that uses training data to create a set of classification rules. In this paper we introduce CON-FOLD which exten…
cs.AI2024★ 4 cited
Automated Theorem Provers Help Improve Large Language Model Reasoning
Lachlan McGinness, Peter Baumgartner
In this paper we demonstrate how logic programming systems and Automated first-order logic Theorem Provers (ATPs) can improve the accuracy of Large Language Models (LLMs) for logic…
cs.CL2024★ 1 cited
Steamroller Problems: An Evaluation of LLM Reasoning Capability with Automated Theorem Prover Strategies
Lachlan McGinness, Peter Baumgartner
This study presents the first examination of the ability of Large Language Models (LLMs) to follow reasoning strategies that are used to guide Automated Theorem Provers (ATPs). We…