  We introduce SparcAssist, a general-purpose risk assessment tool for the
machine learning models trained for language tasks. It evaluates models' risk
by inspecting their behavior on counterfactuals, namely out-of-distribution
instances generated based on the given data instance. The counterfactuals are
generated by replacing tokens in rational subsequences identified by ExPred,
while the replacements are retrieved using HotFlip or
Masked-Language-Model-based algorithms. The main purpose of our system is to
help the human annotators to assess the model's risk on deployment. The
counterfactual instances generated during the assessment are the by-product and
can be used to train more robust NLP models in the future.
