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Character-based Neural Network Translation Github Link Introduction Traditional methods in language modeling involve making an n-th order Markov assumption and estimating n-gram probabilities via counting. The count-based models are simple to train, but due to data sparsity, the probabilities of rare n-grams can be poorly estimated. Neural Language Models (NLM)... [Read More]

Word-Based Neual Machine Translation - Bidirectional LSTM with Multiplicative Attention [Read More]