Instruction Tuned Language Model

Instruction-tuned language models (LLMs) are large language models trained to follow instructions, improving their ability to perform diverse tasks without extensive task-specific training. Current research focuses on enhancing their performance across various modalities (e.g., speech), improving robustness to instruction variations, mitigating safety risks like backdoor attacks and biases, and developing more efficient evaluation metrics. This area is significant because it advances the capabilities of LLMs for real-world applications and provides valuable insights into model behavior, prompting strategies, and the broader challenges of aligning AI systems with human intentions.