Exposure Bias. Regardless of decoding strategy choices, the exposure bias problem [9, 151], defined
as the discrepancy in decoding between training and inference time, can be another contributor to
hallucination. It is common practice to train the decoder with teacher-forced maximum likelihood
estimation (MLE) training, where the decoder is encouraged to predict the next token conditioned on
the ground-truth prefix sequences. However, during the inference generation, the model generates
the next token conditioned on the historical sequences previously generated by itself [69]. Such a
discrepancy can lead to increasingly erroneous generation, especially when the target sequence
gets longer.
SurveyofHallucinationinNatural Language Generation