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20232026
most citedAn Evaluation of ChatGPT-4's Qualitative Spatial Reasoning Capabilities in RCC-8

5 citations · 13 across the 8 of their papers we have counts for

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cs.CL2025

Evaluating the Ability of Large Language Models to Reason about Cardinal Directions, Revisited

Anthony G Cohn, Robert E Blackwell

We investigate the abilities of 28 Large language Models (LLMs) to reason about cardinal directions (CDs) using a benchmark generated from a set of templates, extensively testing a…

cs.CL2025

An Empirical Study of Conformal Prediction in LLM with ASP Scaffolds for Robust Reasoning

Navdeep Kaur, Lachlan McPheat, Alessandra Russo +2

In this paper, we examine the use of Conformal Language Modelling (CLM) alongside Answer Set Programming (ASP) to enhance the performance of standard open-weight LLMs on complex mu…

cs.CL2024★ 1 cited

Can Large Language Models Reason about the Region Connection Calculus?

Anthony G Cohn, Robert E Blackwell

Qualitative Spatial Reasoning is a well explored area of Knowledge Representation and Reasoning and has multiple applications ranging from Geographical Information Systems to Robot…

cs.CL2024★ 4 cited

Towards Reproducible LLM Evaluation: Quantifying Uncertainty in LLM Benchmark Scores

Robert E. Blackwell, Jon Barry, Anthony G. Cohn

Large language models (LLMs) are stochastic, and not all models give deterministic answers, even when setting temperature to zero with a fixed random seed. However, few benchmark s…

cs.CL2024★ 3 cited

Evaluating the Ability of Large Language Models to Reason about Cardinal Directions

Anthony G Cohn, Robert E Blackwell

We investigate the abilities of a representative set of Large language Models (LLMs) to reason about cardinal directions (CDs). To do so, we create two datasets: the first, co-crea…