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This content delves into the concept of decoding in natural language generation (NLG) using RNN Encoder-Decoder models. It discusses decoding approaches such as greedy decoding, sampling from probability distributions, and beam search in RNNs. It also explores applications of decoding and machine tr

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Natural Language Generation (NLG) is the process of constructing natural language outputs from non-linguistic inputs. It involves generating text from machine representations to meet specific communicative goals. NLG is distinct from Natural Language Understanding (NLU) as it maps meaning to text, w

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Cutting-edge research in logical natural language generation (NLG) is transforming the field by moving beyond traditional surface realization to generate summarized text, conclude trends, and apply logical and mathematical operations. By addressing limitations such as lack of logical inference, summ

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