4 citations · 9 across the 8 of their papers we have counts for
8 papers
Large Language Models Imitate Logical Reasoning, but at what Cost?
Lachlan McGinness, Peter Baumgartner
We present a longitudinal study which evaluates the reasoning capability of frontier Large Language Models over an eighteen month period. We measured the accuracy of three leading…
The AlphaPhysics Term Rewriting System for Marking Algebraic Expressions in Physics Exams
Peter Baumgartner, Lachlan McGinness
We present our method for automatically marking Physics exams. The marking problem consists in assessing typed student answers for correctness with respect to a ground truth soluti…
Large Language Models' Reasoning Stalls: An Investigation into the Capabilities of Frontier Models
Lachlan McGinness, Peter Baumgartner
Empirical methods to examine the capability of Large Language Models (LLMs) to use Automated Theorem Prover (ATP) reasoning strategies are studied. We evaluate the performance of S…
Can Large Language Models Correctly Interpret Equations with Errors?
Lachlan McGinness, Peter Baumgartner
This paper explores the potential of Large Language Models to accurately extract and translate equations from typed student responses into a standard format. This is a useful task…
Highlighting Case Studies in LLM Literature Review of Interdisciplinary System Science
Lachlan McGinness, Peter Baumgartner
Large Language Models (LLMs) were used to assist four Commonwealth Scientific and Industrial Research Organisation (CSIRO) researchers to perform systematic literature reviews (SLR…
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…
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…
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…