How do LLMs perform instruction following and why is it difficult?

Instruction following enables LLMs to execute user intent accurately, but it is difficult because natural language instructions are often ambiguous, conflicting, or incomplete.

Instruction following is one of the defining capabilities of modern LLMs.

Unlike raw pretrained models that simply continue text, instruction-tuned models are optimized to:

This capability is achieved through:

Training on datasets containing prompts and ideal responses.

Optimizing outputs according to human preferences.

Providing explicit system instructions.…