Language models enhanced with external knowledge sources, such as embeddings or vector databases, to improve performance in tasks like retrieval and question answering.
More about Augmented Language Models
Augmented Language Models are enhanced versions of traditional language models that incorporate external knowledge sources or retrieval mechanisms. These models integrate resources like knowledge graphs or vector databases to deliver contextually rich and accurate responses.
Augmentation helps address limitations of standalone language models by enabling them to access real-time or domain-specific information, making them ideal for applications like knowledge retrieval and question answering.
