structured-prompts

#structured-prompts

@Vincent_AINotes: Anthropic officially demonstrates a more stable way to write prompts: don't mix background, materials, rules, examples, and output requirements into one paragraph. Instead, assign each type of information a clear position and use XML tags to delineate boundaries. The core idea is not to make prompts longer, but to minimize what the model needs to guess. I've compiled...

X AI KOLs Timeline ↗ · yesterday Cached

Anthropic officially demonstrates a method to structure prompts using XML tags, separating background, materials, rules, examples, and output requirements to reduce guesswork and improve stability.

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#structured-prompts

Dimension-Level Intent Fidelity Evaluation for Large Language Models: Evidence from Structured Prompt Ablation

arXiv cs.CL ↗ · 2026-05-15 Cached

This paper introduces a dimension-level evaluation method for measuring intent fidelity in large language models using structured prompt ablation.

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structured-prompts

Dimension-Level Intent Fidelity Evaluation for Large Language Models: Evidence from Structured Prompt Ablation

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