Modality Conversion

Modality conversion focuses on transforming data between different representational forms (e.g., text, images, speech) to improve AI understanding and generation. Current research heavily utilizes transformer-based architectures, exploring both direct conversion methods and strategies that leverage pre-trained models for specific modalities, sometimes bypassing explicit conversion altogether. This field is significant because it enables the integration of information across diverse data types, leading to improved performance in tasks like fact verification and emotion recognition, and facilitating the development of more versatile and robust AI systems.