KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering. (arXiv:2205.03071v1 [cs.CL])

Web: http://arxiv.org/abs/2205.03071

Extractive Question Answering (EQA) is one of the most important tasks in
Machine Reading Comprehension (MRC), which can be solved by fine-tuning the
span selecting heads of Pre-trained Language Models (PLMs). However, most
existing approaches for MRC may perform poorly in the few-shot learning
scenario. To solve this issue, we propose a novel framework named Knowledge
Enhanced Contrastive Prompt-tuning (KECP). Instead of adding pointer heads to
PLMs, we introduce a seminal paradigm for EQA that transform the task into a …

arxiv knowledge question answering