Selecting The Most Informative Tokens in Natural Language Autoencoders
It is shown that useful explanations can extend beyond the model a verbalizer was trained to describe and show that pretrained verbalizers recover words that models have learned to conceal through fine-tuning, without additional verbalizer training.
Federico Torrielli, Gianluca Barmina, Andrea Blasi Núñez et al.
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