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Nathan Young

2 accepted papers

2024

Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning

ACL 2024findings

Combining large language models with logical reasoning enhances their capacity to address problems in a robust and reliable manner. Nevertheless, the intricate nature of logical reasoning poses challenges when gathering reliable data from the web to build comprehensive training datasets, subsequentl…

2022

AbductionRules: Training Transformers to Explain Unexpected Inputs

ACL 2022findings

Transformers have recently been shown to be capable of reliably performing logical reasoning over facts and rules expressed in natural language, but abductive reasoning - inference to the best explanation of an unexpected observation - has been underexplored despite significant applications to scien…