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한국어(KO) 한국어 질문을 두 번 붙였다 — ‘다시 확인해’와는 결과가 달랐다 한국어 24문항을 두 모델에 한 번, 통째로 두 번, 확인 지시를 붙여 물었다. Luna의 정답은 14/48에서 24/48로 늘었지만 향상은 긴 공지 찾기에 몰렸다. 반대로 틀린 사례와 입력 토큰, 추론 설정의 예외도 함

Prompt repetition boosts LLM accuracy on Korean tasks, but results vary

By PulseAugur Editorial · [1 sources] ·

A recent experiment explored how repeating input prompts affects the performance of large language models like Luna and Claude Haiku 5.5 on Korean language tasks. The study found that duplicating the entire input, including data and instructions, led to an increase in correct answers for Luna, particularly in tasks involving finding specific information in long documents. However, this improvement was not consistent across all tasks, and in some cases, repeating the prompt led to more errors. The findings suggest that while prompt repetition can sometimes enhance LLM accuracy, it does not guarantee better performance and the effects can vary depending on the model and the specific task. AI

IMPACT Prompt repetition may offer a simple method to improve LLM accuracy on specific tasks, but its inconsistent effects necessitate careful testing for each application.

RANK_REASON The item details an experiment comparing LLM performance with repeated prompts, which constitutes research into model capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

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

Prompt repetition boosts LLM accuracy on Korean tasks, but results vary

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The item details an experiment comparing LLM performance with repeated prompts, which constitutes research into model capabilities. [lever_c_demoted from research: ic=1 ai=1.0]
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  1. Mastodon — mastodon.social TIER_1 한국어(KO) · [email protected] ·

    Korean questions were attached twice - the result was different from 'check again'. Korean 24 questions were asked to two models once, twice in total, and with a check instruction. Luna's correct answers increased from 14/48 to 24/48, but the improvement was concentrated in finding long notices. Conversely, there were also exceptions in incorrect cases, input tokens, and inference settings.

    한국어 질문을 두 번 붙였다 — ‘다시 확인해’와는 결과가 달랐다 한국어 24문항을 두 모델에 한 번, 통째로 두 번, 확인 지시를 붙여 물었다. Luna의 정답은 14/48에서 24/48로 늘었지만 향상은 긴 공지 찾기에 몰렸다. 반대로 틀린 사례와 입력 토큰, 추론 설정의 예외도 함께 기록했다. https://zerry.co.kr/blog/prompt-repetition-korean #LLM #프롬프트 #한국어 #실험 #AI

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