The TRAILS project focuses on addressing challenges in natural language processing (NLP) related to linguistic and cultural inclusivity, robustness, and efficiency. Current pre-trained neural models rely on vast amounts of uncurated text data, leading to issues such as cultural bias, underrepresentation of rare languages and phenomena, and overemphasis on large, resource-intensive models. TRAILS aims to improve multilingual and culturally sensitive NLP, enhance fairness and robustness for long-tail phenomena, and develop efficient NLP models to lower resource demands. Funded by the German Federal Ministry of Education and Research, TRAILS seeks to make NLP more inclusive, trustworthy, and sustainable.
