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LLM reasoning order impacts decision accuracy

By PulseAugur Editorial · [1 sources] ·

A language model's output order can significantly impact its decision-making, particularly when generating structured data. When a model is prompted to provide a decision before its reasoning, it essentially defends a pre-determined answer, leading to less accurate outcomes on complex cases. Reversing the order in the schema to place reasoning before the decision prompts the model to generate a more considered and accurate response, as the reasoning then informs the final decision. AI

IMPACT Prompt engineering strategies can influence LLM accuracy, especially in structured output tasks.

RANK_REASON The item discusses a conceptual issue with LLM output generation and prompting strategy, rather than a new release or event.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM reasoning order impacts decision accuracy

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The item discusses a conceptual issue with LLM output generation and prompting strategy, rather than a new release or event.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Serguey Asael Shinder ·

    You Put the Decision Before the Reasoning and the Model Decided First

    <p>The refund assistant<br /> returned structured output.</p> <p>A small schema,<br /> two fields.</p> <p>decision,<br /> approve or refuse.</p> <p>reasoning,<br /> a few sentences<br /> for the person who checks it.</p> <p>The team liked the reasoning.</p> <p>It was careful.</p>…

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