Abstract:We propose a generative model for text generation, which exhibits disentangled latent representations of syntax and semantics. Contrary to previous work, this model does not need syntactic information such as constituency parses, or semantic information such as paraphrase pairs. Our model relies solely on the inductive bias found in attention-based architectures such as Transformers.In the attention of Transformers, keys handle information selection while values specify what information is conveyed. Our model,… Show more
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