4 papers
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…
Learning and Enforcing Context-Sensitive Control for LLMs
Mohammad Albinhassan, Pranava Madhyastha, Mark Law +1
Controlling the output of Large Language Models (LLMs) through context-sensitive constraints has emerged as a promising approach to overcome the limitations of Context-Free Grammar…
: Semantically Controlled Decoding
Mohammad Albinhassan, Pranava Madhyastha, Alessandra Russo
Ensuring both syntactic and semantic correctness in Large Language Model (LLM) outputs remains a significant challenge, despite being critical for real-world deployment. In this pa…
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…