Multilingual AS2

Multilingual Answer Sentence Selection (AS2) focuses on automatically identifying the best sentence(s) answering a given question across multiple languages. Research currently emphasizes overcoming the scarcity of multilingual training data, employing techniques like cross-lingual knowledge distillation and leveraging large language models (LLMs) for data augmentation and model training. Transformer-based architectures are prevalent, with ongoing efforts to improve their performance through specialized pre-training objectives that better capture contextual information. Advances in multilingual AS2 are crucial for building more inclusive and effective question answering systems that can serve a broader range of users and languages.