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Study: Prompt position and authority influence LLM answers

By PulseAugur Editorial · [2 sources] ·

A new study published on arXiv explores how to influence language models' answers, finding that the position of advice within a prompt significantly impacts its effectiveness. The research indicates that advice placed just before a model's response is most detrimental, while advice with a false rationale is most harmful when presented early in the prompt. Attributing advice to an authority figure or phrasing it assertively also increases error rates, with the study releasing code and data for further investigation. AI

IMPACT This research could inform prompt engineering strategies to improve LLM reliability and safety.

RANK_REASON The cluster contains a research paper detailing findings on influencing language model behavior.

Read on Hugging Face Daily Papers →

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

Study: Prompt position and authority influence LLM answers

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COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Xinyi Ni ·

    Position Matters More Than Channel: Talking a Language Model Out of a Correct Answer

    arXiv:2610.34809v1 Announce Type: new Abstract: Language models now answer questions alongside other claims: a note in the system prompt, a message from another agent, their own earlier answer. We ask what it takes to talk a model out of an answer it gets right on its own, and se…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Position Matters More Than Channel: Talking a Language Model Out of a Correct Answer

    Language models now answer questions alongside other claims: a note in the system prompt, a message from another agent, their own earlier answer. We ask what it takes to talk a model out of an answer it gets right on its own, and separate three factors that earlier studies vary t…

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