715 citations · 867 across the 11 of their papers we have counts for
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cs.CL2022★ 1 cited
Prompt Compression and Contrastive Conditioning for Controllability and Toxicity Reduction in Language Models
David Wingate, Mohammad Shoeybi, Taylor Sorensen
We explore the idea of compressing the prompts used to condition language models, and show that compressed prompts can retain a substantive amount of information about the original…
cs.CL2022★ 40 cited
Leveraging Large Language Models for Multiple Choice Question Answering
Joshua Robinson, Christopher Michael Rytting, David Wingate
While large language models (LLMs) like GPT-3 have achieved impressive results on multiple choice question answering (MCQA) tasks in the zero, one, and few-shot settings, they gene…