Compositional Language Understanding with Text-based Relational Reasoning

7 Nov 2018Koustuv Sinha • Shagun Sodhani • William L. Hamilton • Joelle Pineau

Neural networks for natural language reasoning have largely focused on extractive, fact-based question-answering (QA) and common-sense inference. However, it is also crucial to understand the extent to which neural networks can perform relational reasoning and combinatorial generalization from natural language---abilities that are often obscured by annotation artifacts and the dominance of language modeling in standard QA benchmarks. In this work, we present a novel benchmark dataset for language understanding that isolates performance on relational reasoning.

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