Rephrase and Respond (RaR)
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Paper summary
An effective prompting method where the LLM rephrases and expands the user's question before answering it.
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01
Rephrase step: The model first rewrites the question to resolve ambiguity, fill in implicit assumptions, and make the task explicit - then answers the rephrased version.
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Broad task gains: Improves performance across diverse tasks without needing any fine-tuning, using only prompt-level changes.
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Stacks with CoT: Combines cleanly with chain-of-thought prompting, giving additive improvements on reasoning benchmarks.
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User-friendly interpretation: Shows that part of the "prompt engineering" skill gap between novice and expert users is really a rephrasing problem - one the LLM itself can fix.