Efficient Search for Transformation-based Inference

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Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets (2019, background): “Pre-neural systems often included explicit components, such as engineered features or syntax-based transformations (e.g. Stern and Dagan, 2012; Stern et al., 2012; Bar-Haim et al., 2015), to address particular inference types such as syntactic, lexical, and logical inferences.”
Question Answering as Global Reasoning Over Semantic Abstractions (2018, background): “Bar-Haim, Dagan, and Berant (2015) and Stern et al. (2012) search over a space of a pre-deﬁned set of text transformations (e.g., coreference substitutions, passive to active).”
The Excitement Open Platform for Textual Inferences (2014, background): “In addition, it includes a search algorithm which ﬁnds an optimal sequence of transformations for any given T/H pair (Stern et al., 2012).”