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REER Reverse Reasoning Guide

REER, or Reverse-Engineered Reasoning, is a new way to teach AI models how to think deeply and step-by-step for open-ended tasks like writing stories or essays. Unlike traditional methods that build reasoning from scratch, REER starts with a high-quality final answer and works backward to uncover the hidden thinking process that could have led to it. This creates useful "reasoning trajectories"—detailed paths of thought—for training AI to handle creative, unstructured problems.

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Example

Imagine the task: "Write a short story about a lost explorer." A high-quality output y is a vivid tale of adventure and discovery.

  • Initial Trajectory z: "Think of a jungle setting. Add a hero. End with finding treasure."
  • Refinement: Perplexity is high (AI finds y surprising). Tweak the first segment: "Plan the plot: Explorer gets lost in Amazon, faces dangers like rivers and animals. Hmm... Alternatively, include a mysterious guide." Recheck perplexity—lower now, as it better leads to y's details.
  • Final z: "Outline key events: Start with excitement of expedition. Build tension with isolation and clues. Explore alternatives: What if the treasure is knowledge, not gold? Self-correct: Wait, that's too vague—focus on emotional growth. Conclude with reflection." This path now makes y feel like a natural outcome.
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