#fault-injection News & Analysis

3 articles tagged with #fault-injection. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 97/10

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SENTRY: Statistical Reliability Analysis of Vision Transformers Under Soft Errors

Researchers present SENTRY, a statistical fault injection framework that efficiently evaluates Vision Transformers' reliability against soft errors in safety-critical applications. The method achieves formal reliability guarantees using finite-population sampling theory, reducing experimental costs by up to 10,700x while identifying critical vulnerabilities in normalization layers and IEEE-754 exponent bits.

AINeutralarXiv – CS AI · Jun 26/10

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Not All Errors Are Equal: A Systematic Study of Error Propagation in Large Language Model Inference

Researchers present LLMFI, a fault-injection framework that systematically studies how hardware errors propagate through large language model inference across multiple domains. The study identifies critical vulnerability patterns and proposes four software-only reliability improvements, providing practical guidance for deploying LLMs in high-performance computing environments.

AINeutralarXiv – CS AI · Apr 146/10

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The Weight of a Bit: EMFI Sensitivity Analysis of Embedded Deep Learning Models

Researchers demonstrate that embedded neural network models using integer representations (8-bit and 4-bit) are significantly more resilient to electromagnetic fault injection attacks than floating-point formats (32-bit and 16-bit). The study reveals that floating-point models experience near-complete accuracy degradation from a single fault, while 8-bit integer representations maintain robust performance, with implications for securing AI systems deployed on edge devices.