7 citations · 11 across the 6 of their papers we have counts for
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cs.LG2019
Generalization in Generation: A closer look at Exposure Bias
Florian Schmidt
Exposure bias refers to the train-test discrepancy that seemingly arises when an autoregressive generative model uses only ground-truth contexts at training time but generated ones…
cs.LG2019
Autoregressive Text Generation Beyond Feedback Loops
Florian Schmidt, Stephan Mandt, Thomas Hofmann
Autoregressive state transitions, where predictions are conditioned on past predictions, are the predominant choice for both deterministic and stochastic sequential models. However…