139 citations · 373 across the 15 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.CL2021
Retrieval-guided Counterfactual Generation for QA
Bhargavi Paranjape, Matthew Lamm, Ian Tenney
Deep NLP models have been shown to learn spurious correlations, leaving them brittle to input perturbations. Recent work has shown that counterfactual or contrastive data -- i.e. m…
cs.CL2021★ 17 cited
The MultiBERTs: BERT Reproductions for Robustness Analysis
Thibault Sellam, Steve Yadlowsky, Jason Wei +9
Experiments with pre-trained models such as BERT are often based on a single checkpoint. While the conclusions drawn apply to the artifact tested in the experiment (i.e., the parti…