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H-infinity controller improves LLM steering

Original title: Mind Control of LLMs via Closed-Loop Stimulation: Out-of-Distribution Robustness

arXiv cs.AI / cs.LG / cs.CLby Kasra Fallah ()1 min read
AI summary · x-ai/grok-4.7Summaries by Vani AI

H∞ controller enhances robustness for out-of-distribution LLM steering.

LLM steering is formulated as a feedback-control problem. The H∞-based controller limits sensitivity to disturbances. It improves performance over baselines especially under out-of-distribution conditions. A new robust steerability measure S_rob is introduced.

Key facts
  • H∞ controller developed
  • Gains on steering benchmarks
  • Significant OOD improvements
  • S_rob pre-deployment measure
  • Varies with model scale
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From the original article

1 min read at arxiv.org

Brains and large language models need not be considered equivalent systems to reveal an interpretable commonality: both exhibit high-dimensional, nonlinear dynamics whose behavior can only be modeled imperfectly. This creates a shared challenge whenever we seek to intervene in their dynamics.

arXiv cs.AI / cs.LG / cs.CL

By Kasra Fallah · arxiv.org

Read the full article at arXiv cs.AI / cs.LG / cs.CL

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