TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing

Understand

Various robustness evaluation methodologies from different perspectives have been proposed for different natural language processing (NLP) tasks.

• These methods have often focused on either universal or task-specific generalization capabilities.
• In this work, we propose a multilingual robustness evaluation platform for NLP tasks (TextFlint) that incorporates universal text transformation, task-specific transformation, adversarial attack, subpopulation, and their combinations to provide comprehensive robustness analysis.
• TextFlint enables practitioners to automatically evaluate their models from all aspects or to customize their evaluations as desired with just a few lines of code.