4 citations · 7 across the 2 of their papers we have counts for
3 papers
cs.LG2024
I Don't Know: Explicit Modeling of Uncertainty with an [IDK] Token
Roi Cohen, Konstantin Dobler, Eden Biran +1
Large Language Models are known to capture real-world knowledge, allowing them to excel in many downstream tasks. Despite recent advances, these models are still prone to what are…
cs.CL2023★ 4 cited
LM vs LM: Detecting Factual Errors via Cross Examination
Roi Cohen, May Hamri, Mor Geva +1
A prominent weakness of modern language models (LMs) is their tendency to generate factually incorrect text, which hinders their usability. A natural question is whether such factu…
cs.CL2023★ 3 cited
Crawling the Internal Knowledge-Base of Language Models
Roi Cohen, Mor Geva, Jonathan Berant +1
Language models are trained on large volumes of text, and as a result their parameters might contain a significant body of factual knowledge. Any downstream task performed by these…