Informativeness and Invariance: Two Perspectives on Spurious Correlations in Natural Language. (arXiv:2204.04487v2 [cs.CL] UPDATED)

Web: http://arxiv.org/abs/2204.04487

Spurious correlations are a threat to the trustworthiness of natural language
processing systems, motivating research into methods for identifying and
eliminating them. However, addressing the problem of spurious correlations
requires more clarity on what they are and how they arise in language data.
Gardner et al (2021) argue that the compositional nature of language implies
that \emph{all} correlations between labels and individual "input features" are
spurious. This paper analyzes this proposal in the context of a toy example,
demonstrating three …

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