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Posing Fair Generalization Tasks for Natural Language Inference
Deep learning models for semantics are generally evaluated using naturalistic corpora.
Recursive Routing Networks: Learning to Compose Modules for Language Understanding
The model jointly optimizes the parameters of the functions and the meta-learner{'}s policy for routing inputs through those functions.
Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences
Standard evaluations of deep learning models for semantics using naturalistic corpora are limited in what they can tell us about the fidelity of the learned representations, because the corpora rarely come with good measures of semantic complexity.
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