UNMASK: Automated Detection and Mitigation of Spurious Text Correlations

UNMASK is an automated pipeline that discovers and causally verifies spurious surface patterns in text classifiers. It uses boolean expressions to identify features that boost benchmarks without providing true linguistic or causal relevance, enabling mitigation without manual annotation.