Cross Lingual Information Retrieval

Cross-lingual information retrieval (CLIR) aims to overcome language barriers in information search by retrieving documents in one language using queries from another. Current research heavily utilizes large language models (LLMs) and multilingual transformer architectures, often employing techniques like knowledge distillation, contrastive learning, and multi-stage ranking/reranking to improve retrieval accuracy, particularly for low-resource languages. These advancements are significant for broadening access to information globally and improving the efficiency of multilingual search engines and other applications requiring cross-lingual information access.