Research Topics
Our interest lies in enabling technologies for intelligent retrieval and mining data/document/object retrieval systems. We are pursuing research in the following directions.
This area of our research focuses on developing algorithms and systems for information retrieval. Our aim is to enhance the efficiency, relevance, and speed of accessing information across various domains.
Our work in multilingual language models revolves around creating models capable of understanding and generating human languages across diverse linguistic landscapes. We're dedicated to developing versatile systems that facilitate communication and understanding across global boundaries.
In multimodal learning, we explore the fusion of vision and language through advanced algorithms and systems. Our research aims to bridge the gap between different data types, enabling machines to interpret and generate information from various sources. This interdisciplinary approach holds promise for natural language understanding.
Our focus in code generation encompasses the development of algorithms and systems tailored for various tasks, including code summarization and translation. We streamline development processes, automate tasks, and enhance code quality and comprehension.