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This work develops and publishes a series of sequence-to-sequence data sets that correspond to the theorem proving tasks using several encodings, and provides the first experimental evaluation of the performance of recurrent neural networks on such tasks. Expand

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In this paper we present a new approach for solving quantified formulas in Satisfiability Modulo Theories (SMT), with a particular focus on the theory of fixed-size bit-vectors. We combine… Expand

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We study the worst-case time complexity of relational programs for the canonical implementation of miniKanren. We propose a model that breaks the evaluation time in miniKanren into several different… Expand

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