Active PETs: Active Data Annotation Prioritisation for Few-Shot Claim Verification with Pattern Exploiting Training. (arXiv:2208.08749v2 [cs.CL] UPDATED)

To mitigate the impact of the scarcity of labelled data on fact-checking
systems, we focus on few-shot claim verification. Despite recent work on
few-shot classification by proposing advanced language models, there is a
dearth of research in data annotation prioritisation that improves the
selection of the few shots to be labelled for optimal model performance. We
propose Active PETs, a novel weighted approach that utilises an ensemble of
Pattern Exploiting Training (PET) models based on various language models, to
actively …

annotation arxiv data data annotation training verification