Multilingual Semantic

Multilingual semantic search aims to retrieve relevant information across multiple languages, requiring sophisticated models that understand meaning beyond literal translation. Current research focuses on developing robust methods for handling low-resource languages and mitigating language bias, often employing techniques like meta-learning and multi-concept parsing frameworks built upon pre-trained language models. These advancements are crucial for improving cross-lingual information access and enabling more effective applications in areas such as question answering, search engines, and cross-cultural communication.