Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce Data Annotation Required in Visual Commonsense Tasks. (arXiv:2204.11922v1 [cs.CL])

Pre-trained language models have shown excellent results in few-shot learning
scenarios using in-context learning. Although it is impressive, the size of
language models can be prohibitive to make them usable in on-device
applications, such as sensors or smartphones. With smaller language models,
task-specific data annotation is needed to fine-tune the language model for a
specific purpose. However, data annotation can have a substantial financial and
time burden for small research groups, startups, and even companies. In this
paper, we analyze …

annotation arxiv data data annotation independent reduce