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Training semantic parsers from weak supervision (denotations) rather than strong supervision (programs) complicates training in two ways.
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Globally normalized transition-based neural networks
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Clevr: A diagnostic dataset for compositional language and elementary visual reasoning
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Inferring and executing programs for visual reasoning
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Neural semantic parsing with type constraints for semi-structured tables
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Neural symbolic machines: Learning semantic parsers on Freebase with weak supervision
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