22 citations · 39 across the 3 of their papers we have counts for
3 papers
cs.CR2023★ 1 cited
Does Prompt-Tuning Language Model Ensure Privacy?
Shangyu Xie, Wei Dai, Esha Ghosh +3
Prompt-tuning has received attention as an efficient tuning method in the language domain, i.e., tuning a prompt that is a few tokens long, while keeping the large language model f…
q-bio.NC2019★ 22 cited
Inducing brain-relevant bias in natural language processing models
Dan Schwartz, Mariya Toneva, Leila Wehbe
Progress in natural language processing (NLP) models that estimate representations of word sequences has recently been leveraged to improve the understanding of language processing…
cs.CL2019★ 16 cited
Understanding language-elicited EEG data by predicting it from a fine-tuned language model
Dan Schwartz, Tom Mitchell
Electroencephalography (EEG) recordings of brain activity taken while participants read or listen to language are widely used within the cognitive neuroscience and psycholinguistic…