Adaptive Instruction Composition for Automated LLM Red-Teaming

📰 ArXiv cs.AI

Learn to improve LLM red-teaming with adaptive instruction composition, enhancing attack strategy discovery

advanced Published 25 Apr 2026

Action Steps

Implement adaptive instruction composition to generate effective attack strategies for LLM red-teaming
Combine crowdsourced harmful queries and tactics into instructions for the attacker LLM
Use trial and error to identify successful attacks and refine the instruction composition process
Evaluate the effectiveness of the adaptive instruction composition approach against existing methods
Apply the discovered attack strategies to improve the robustness of target LLMs

Who Needs to Know This

AI engineers and researchers can benefit from this technique to strengthen their LLMs against potential attacks and improve overall security

Key Insight

💡 Adaptive instruction composition can enhance the discovery of effective attack strategies for LLM red-teaming, improving overall security

Key Takeaways

Learn to improve LLM red-teaming with adaptive instruction composition, enhancing attack strategy discovery

Full Article

Title: Adaptive Instruction Composition for Automated LLM Red-Teaming

Abstract:
arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifying effective strategies through trial and error, resulting in a semantically limited range of successes. Another approach discovers diverse attacks by combining crowdsourced harmful queries and tactics into instructions for the attacker, but does so at random, limiting effectiveness. This article int

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