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Changing the Mind of Transformers for Topically-Controllable Language Generation
Our framework consists of two components: (1) a method that produces a set of candidate topics by predicting the centers of word clusters in the possible continuations, and (2) a text generation model whose output adheres to the chosen topics.
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