Instruct Tuned Model

Instruct-tuned models are large language models (LLMs) specifically trained to follow instructions, improving their ability to generate helpful and relevant responses compared to foundation models. Current research focuses on mitigating biases in these models and their evaluators, enhancing their reasoning capabilities through techniques like retrieval-augmented generation (RAG), and improving their performance on tasks involving visual information or code generation by incorporating external knowledge sources and static analysis. This work is significant because it addresses critical limitations of LLMs, leading to more reliable and robust AI systems with broader applications in various fields.