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Guidance And Control Tokens documentation

Guidance and Control Tokens

Abstract

Use system/prefix tokens, stop sequences, negative prompts, and guidance tokens to steer model behavior without changing weights.

Motivation

  • Enforce style, length, or safety behaviors
  • Condition diffusion models via classifier-free guidance or text conditioning

Architectures

  • System/prefix instructions + stop sequences
  • Control tokens (e.g., style/safety tokens) where models support them
  • Diffusion guidance scales for image/video

Design Choices

  • Strength of guidance vs. creativity
  • Stop sequences and delimiters for termination
  • Safety tokens and content filters

Pros/Cons

  • Pros: Lightweight control, no retraining
  • Cons: Provider-specific tokens; brittle across versions

Evaluation Metrics

  • Adherence to style/length constraints
  • Safety violation rates

Vendor/Tooling

  • Provider system prompts; negative prompts for diffusion
  • JSON mode/Schema as guidance for structure

Design Checklist

  • Define allowed styles/tone and stop rules
  • Test stability across decoding settings
  • Combine with structured output validation

References

  • Title: OpenAI Prompt engineering URL: https://platform.openai.com/docs/guides/prompt-engineering Publisher/Vendor: OpenAI Accessed: 2025-08-14 Version_or_release: provider_reported
  • Title: Stable Diffusion guidance (Diffusers) URL: https://huggingface.co/docs/diffusers/index Publisher/Vendor: Hugging Face Accessed: 2025-08-14 Version_or_release: provider_reported