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License: MIT License
Hi. Your idea of modeling complex sequences via so-called self-boost refinement is very interesting.
I tried to implement this approach to neural machine translation. That is, train an autoregressive model
However, I found that, since this is not an end-to-end procedure, the validation loss goes higher as the Castep
increases. The expectation that the later model corrects the wrong part of the previous prediction according to other parts it depends on
fails. This result is not a surprise to me because the model can easily find a shortcut which is just simply copying the inputs and this shortcut conveniently maintains a good likelihood loss. In other words, in my implementation, only the first model
So I am wondering how exactly CASR model can achieve refinement
.
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