Instruction following is a model's ability to comply with directives given in natural language while respecting system and safety constraints.
Evaluation Benchmarks
Prompt Anatomy
Design Trade-offs
- Adding more few-shot examples boosts accuracy but consumes tokens.
- High temperature encourages creativity but risks deviating from instructions.
- Overly strict system prompts can override user intent.
Current Trends (2025)
- Hierarchical prompting reserves first 200 tokens for safety and style then appends dynamic context.
- Instruction-fine-tuned open models (Hermes-2 Pro) reach GPT-3.5 compliance at 1/10th cost.
- LLMs self-generate synthetic instruction datasets for continual tuning.
Implementation Tips
- Test with adversarial paraphrases to ensure robustness.
- Keep safety rules earlier than task to maintain precedence.
- Log refused requests separately to improve policy coverage.