Towards Red Teaming in Multimodal and Multilingual Translation

Anonymous

Abstract: This paper presents the first study on human-based red teaming for Machine Translation (MT), marking a significant step towards understanding and improving the performance of translation models. We delve into both human-based red teaming and a study on automation, reporting lessons learned and providing recommendations for both translation models and red teaming drills. This pioneering work opens up new avenues for research and development in the field of MT

Paper Type: short

Research Area: Resources and Evaluation

Contribution Types: Model analysis & interpretability

Languages Studied: German, French, Spanish and Italian