activity
20242026
collaborators

5 papers

cs.AI2026

DecompSR: A dataset for decomposed analyses of compositional multihop spatial reasoning

Lachlan McPheat, Navdeep Kaur, Robert Blackwell +3

We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse compositional spatial reasoning abi…

cs.AI2026

QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi

Anthony G. Cohn, Robert E. Blackwell

We introduce an extensive qualitative spatial and temporal reasoning (QSTR) benchmark for evaluating large language models (LLMs). We pose questions concerning compositional reason…

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

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

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…