Improved and Efficient Conversational Slot Labeling through Question Answering. (arXiv:2204.02123v1 [cs.CL])

Transformer-based pretrained language models (PLMs) offer unmatched
performance across the majority of natural language understanding (NLU) tasks,
including a body of question answering (QA) tasks. We hypothesize that
improvements in QA methodology can also be directly exploited in dialog NLU;
however, dialog tasks must be \textit{reformatted} into QA tasks. In
particular, we focus on modeling and studying \textit{slot labeling} (SL), a
crucial component of NLU for dialog, through the QA optics, aiming to improve
both its performance and efficiency, and …

arxiv conversational labeling question answering