Universal Semantic

Universal semantic research aims to identify and represent the core meanings shared across languages and modalities, facilitating cross-lingual understanding and improved AI systems. Current efforts focus on developing robust multilingual models, often employing Expectation-Maximization-like algorithms or cascade architectures, to learn these universal representations from large datasets, even in the presence of limited parallel data. This work is crucial for advancing natural language processing, improving machine translation and text-to-image generation, and mitigating ethical concerns arising from biases in AI models.