1 code implementation • 16 Apr 2021 • Joe Stacey, Yonatan Belinkov, Marek Rei
Natural Language Inference (NLI) models are known to learn from biases and artefacts within their training data, impacting how well they generalise to other unseen datasets.
1 code implementation • EMNLP 2020 • Joe Stacey, Pasquale Minervini, Haim Dubossarsky, Sebastian Riedel, Tim Rocktäschel
Natural Language Inference (NLI) datasets contain annotation artefacts resulting in spurious correlations between the natural language utterances and their respective entailment classes.