1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2022★ 1 cited
Do ever larger octopi still amplify reporting biases? Evidence from judgments of typical colour
Fangyu Liu, Julian Martin Eisenschlos, Jeremy R. Cole +1
Language models (LMs) trained on raw texts have no direct access to the physical world. Gordon and Van Durme (2013) point out that LMs can thus suffer from reporting bias: texts ra…
cs.CL2022
WinoDict: Probing language models for in-context word acquisition
Julian Martin Eisenschlos, Jeremy R. Cole, Fangyu Liu +1
We introduce a new in-context learning paradigm to measure Large Language Models' (LLMs) ability to learn novel words during inference. In particular, we rewrite Winograd-style co-…