AIMPACT reports that Amazon scientists have proposed an automated prompt engineering framework called Promptimus, which can improve high-quality LLM prompts without human intervention. By iteratively optimizing strategies and auxiliary optimizer models to analyze the interaction between prompts and model outputs, it automatically adjusts aspects such as instruction clarity and example selection. Multiple benchmarks show an average improvement of 5-15%, with GSM8K math reasoning increasing from 78% to 85%, covering tasks like commonsense question answering and code generation. The framework is versatile, not dependent on specific LLM architectures or tasks, and uses regularization and cross-validation to prevent over-optimization, ensuring generalization ability.

MeNews

2026-05-21 03:33:07

Abstract generation in progress

AIMPACT News, May 15 (UTC+8), Amazon scientists proposed an automated prompt engineering framework called Promptimus, which can improve existing high-quality LLM prompts without human intervention. The method uses an iterative optimization strategy, leveraging an auxiliary "optimizer" model to analyze the interaction patterns between prompts and model outputs, automatically identifying and adjusting aspects such as instruction clarity and example selection. In multiple benchmark tests including mathematical reasoning (GSM8K accuracy increased from 78% to 85%), commonsense question answering, and code generation, the optimized prompts showed an average performance improvement of 5%-15%. This framework does not rely on specific LLM architectures or task types, making it versatile, and it incorporates regularization terms and cross-validation mechanisms to prevent overfitting, ensuring generalization ability. (Source: InFoQ)

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AutumnTranquility

· 8h ago

Can common sense Q&A also increase? That indicates it's not just format tuning; it's truly making progress at the comprehension level.

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GateUser-6319729f

· 10h ago

Auto-tuning prompts finally no longer requires alchemy.

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GateUser-9076f8b9

· 11h ago

Regularization + cross-validation to prevent overfitting, data scientists will nod when they see this line

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GammaRunner

· 11h ago

5-15% average improvement in listening is modest, but consider this is zero-shot automatic optimization, saving a lot of manual effort.

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IceCreamUnderTheNeonLights

· 11h ago

Amazon is paving the way for its own AWS Bedrock this time, with a general framework + architecture independence, showing quite an ambition.

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GateUser-656cc6e4

· 11h ago

Wait, should the auxiliary optimizer model itself be tuned? Recursive warning

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PocketValidator

· 11h ago

The name Promptimus has a strong cyber vibe, and the effect looks quite solid. A 7-point increase in GSM8K is no small feat.

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Amazon releases the Promptimus framework, automatically optimizing LLM prompts

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