Developing more robust NLI models that generalise better to other unseen datasets

The PhD will involve developing strategies to help models rely less on biases or artefacts within their training data, allowing the models to generalise better to unseen data without the same biases or artefacts. The thesis will focus on the task of Natural Language Inference, training models on a single dataset in a more robust way that will improve zero-shot performance on other NLI datasets.

General Topic: data science.