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Machine learning models such as Transformers or LSTMs struggle with tasksthat are compositional in nature such as those involving reasoning/inference.Although many datasets exist to evaluate compositional generalization, when itcomes to evaluating inference abilities, options are more limited. This paperpresents LogicInference, a new dataset to evaluate the ability of models toperform logical inference. The dataset focuses on inference using propositionallogic and a small subset of first-order logic, represented both in semi-formallogical notation, as well as in natural language. We also report initialresults using a collection of machine learning models to establish an initialbaseline in this dataset.

LogicInference: A New Dataset for Teaching Logical Inference to seq2seq Models