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Prompt Design at Scale: How Format, Instruction Count, and Context Length Shape Instruction Adherence and Hallucination in Large Language Models
arXiv cs.AI · 发布于 · 阅读约3分钟
30秒读懂
- 发生了什么
- Study tests how instruction count, format, and context length affect LLM compliance and hallucination across five models using a controlled synthetic corpus.
- 为何重要
- Matters for engineers building production systems who need empirical guidance on prompt design choices currently made with little evidence.
- 注意
- Results are model-specific and sometimes contradict expectations; markdown showed no consistent advantage, and token overhead varies by format and context length.
收听本摘要
- language model
- prompt
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