Case-Based Abductive Natural Language Inference. (arXiv:2009.14539v4 [cs.AI] UPDATED)

Most of the contemporary approaches for multi-hop Natural Language Inference
(NLI) construct explanations considering each test case in isolation. However,
this paradigm is known to suffer from semantic drift, a phenomenon that causes
the construction of spurious explanations leading to wrong conclusions. In
contrast, this paper proposes an abductive framework for multi-hop NLI
exploring the retrieve-reuse-refine paradigm in Case-Based Reasoning (CBR).
Specifically, we present Case-Based Abductive Natural Language Inference
(CB-ANLI), a model that addresses unseen inference problems by analogical
transfer …

arxiv case inference language natural natural language