Latest Natural Language Generation Research Introduces ‘Typical Sampling,’ A New Decoding Method that is Principled, Effective, and can be Implemented Efficiently

Natural language models can model a text corpus C by learning the probability distribution p over all natural language strings Y∈C, with Y={y_1,y_2,y_3…,y_t}. For each word y_t, the model learns to output a probability distribution q over candidate words y∈V, the model’s vocabulary, choosing the words which minimize the log-likelihood of q(Y), which is the […]

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