Abstract The field of NLP is in the midst of a disruptive shift, fueled most recently by the advent of large language models (LLMs), with impacts on our methodologies, funding and public perception. While the[...]

Abstract Any valuable NLP dataset has traditionally been shipped with crowdsourced categorical labels. Instructions for collecting these labels are easy to communicate and the labels themselves are easy to annotate. However, as self-supervision based methods[...]