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Found 2 papers, 2 papers with code
Local-Global MCMC kernels: the best of both worlds
Recent works leveraging learning to enhance sampling have shown promising results, in particular by designing effective non-local moves and global proposals.
Implicit Unlikelihood Training: Improving Neural Text Generation with Reinforcement Learning
Likelihood training and maximization-based decoding result in dull and repetitive generated texts even when using powerful language models (Holtzman et al., 2019).
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