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LLMs struggle with information in long prompts, research finds · 2 sources tracked

By PulseAugur Editorial · [2 sources] ·

Researchers have identified a phenomenon called "lost in the middle" where large language models struggle to recall information presented in the middle of long prompts, performing worse than if the information was omitted entirely. Studies show models exhibit "primacy bias" and "recency bias," meaning they best recall information at the beginning and end of a prompt, respectively. This effect persists even with larger context windows, and while newer models show improvement, careful placement of critical information is still advised for optimal performance in retrieval-augmented generation tasks. AI

IMPACT Effective prompt design requires strategic placement of key information to overcome LLM recall limitations, impacting RAG performance.

RANK_REASON The cluster discusses findings from academic papers on LLM behavior.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLMs struggle with information in long prompts, research finds · 2 sources tracked

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48 / 100
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Research
The cluster discusses findings from academic papers on LLM behavior.
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2 independent sources
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paper, other
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High
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Breaking (< 6h)
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COVERAGE [2]

  1. dev.to — LLM tag TIER_1 English(EN) · Ryan Cole ·

    Stop writing prompts like prose: the 4-part contract that kills LLM drift

    <p>Most "prompt engineering" advice is about phrasing. The real problem is that people write prompts the way they write emails — as prose — and then act surprised when the model "drifts" between runs.</p> <p>Production prompts aren't prose. They're contracts. A contract has to de…

  2. dev.to — LLM tag TIER_1 English(EN) · M.T.Ramkrushna ·

    Lost in the Middle: Why LLMs Miss What's Buried in Long Prompts (and How to Fix It)

    <p>You paste a 40-page policy doc into the prompt, ask one question, and the model confidently answers as if page 19 doesn't exist. The fact you needed was right there. It just happened to be in the middle.</p> <p>That's not bad luck. It's a well-measured pattern called <strong>l…

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