MERaLiON

Multimodal Empathetic Reasoning and Learning in One Network (MERaLiON)

MERaLiON is part of Singapore's National Multimodal Large Language Model (LLM) Programme to expand Singapore's capabilities in Artificial Intelligence (AI) research and innovation.The Programme was launched in collaboration with Singapore's Infocomm Media Development Authority (IMDA) and AI Singapore (AISG), leveraging on the high-performance computing resources from the National Supercomputing Centre (NSCC) Singapore.

A cornerstone of this Programme is the development of multimodal LLMs that are localized for Singapore and the region to understand context and values related to the diverse cultures and languages of Southeast Asia.

MERaLiON draws on Institute for Infocomm Research's (I2R) transformative work in speech and language research that has been widely applied in language transcription and translation to support various public agencies and private sector companies.

Developed to enhance the understanding of human communication dynamics through its multimodal integration, MERaLiON marks a significant leap forward in building the next bounds of AI capabilities for Singapore and the Southeast Asia region.

WHY MERaLiON

For better contextual understanding and versatility across different tasks, MERaLiON harnesses cutting-edge AI techniques to process and learn complementary patterns from diverse data sources in a single unified framework.The data sources include various forms of verbal, visual, auditory and audiovisual communication.

MERaLiON series excel in speech summarization, stance detection, inference, and contextual understanding, making it a versatile tool to power applications that demand deep understanding of context, intent, and interpretation of speech cues and paralinguistics nuances.

Key Features

We have designed our data pipelines, model training, and evaluation frameworks with a strong emphasis on scalability, robustness, and adaptability, ensuring the model's effectiveness across different tasks and environments.

The 1st phase leverages on multimodal and multilingual representation learning, alignment for more effective training and better model generalization to comprehend colloquial language and solve downstream tasks.Unique to MERaLiON, the model caters for code-switching and offers key features that include:

Potential Use Cases