Instruction Following
An LLM's ability to accurately understand and execute user instructions, including format, constraints, and intent.
Overview
Instruction following measures how well a language model adheres to user requests, including content requirements, output format specifications, length constraints, persona adoption, and multi-step task execution. It's a core capability that determines a model's practical usefulness.
Training Approaches
Models are trained for instruction following through supervised fine-tuning on instruction-response pairs (SFT), reinforcement learning from human feedback (RLHF), and constitutional AI methods. Evaluation benchmarks include IFEval, MT-Bench, and AlpacaEval, which test adherence to specific formatting and content constraints.