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Found 4 papers, 2 papers with code
Sampling from Discrete Energy-Based Models with Quality/Efficiency Trade-offs
We show that we can sample from such EBMs with arbitrary precision at the cost of sampling efficiency.
Sampling-Based Approximations to Minimum Bayes Risk Decoding for Neural Machine Translation
The mode and other high-probability translations found by beam search have been shown to often be inadequate in a number of ways.
Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation
We argue that the evidence corroborates the inadequacy of MAP decoding more than casts doubt on the model and its training algorithm.
Auto-Encoding Variational Neural Machine Translation
We present a deep generative model of bilingual sentence pairs for machine translation.
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