Better Few-Shot Relation Extraction with Label Prompt Dropout. (arXiv:2210.13733v1 [cs.CL])

Few-shot relation extraction aims to learn to identify the relation between
two entities based on very limited training examples. Recent efforts found that
textual labels (i.e., relation names and relation descriptions) could be
extremely useful for learning class representations, which will benefit the
few-shot learning task. However, what is the best way to leverage such label
information in the learning process is an important research question. Existing
works largely assume such textual labels are always present during both
learning and …

arxiv dropout extraction