mlsanityData to 7 Oct 2026

CheckOne: Lightweight Fault Detection and Mitigation for Vision Transformers

arXiv 2608.04035 ↗First posted 3 Aug 2026cs.AR cs.AIcited by 0

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Abstract (arXiv)

The wide adoption of Vision Transformers (ViTs) in safety-critical applications raises reliability concerns related to hardware faults. Algorithm-Based Fault Tolerance (ABFT) methods have emerged as lightweight and symmetric protection mechanisms for DNNs. However, they are particularly challenging for ViTs due to their significant computational requirements. This work comprehensively evaluates the reliability of ViTs, emphasizing the need for symmetric protection in their layers. Furthermore, we present CheckOne, a novel, cost-effective method for fault detection and mitigation in ViTs that significantly reduces the computational cost compared to conventional ABFT. Through extensive experiments with multiple ViTs, CheckOne mitigates critical faults by up to 26× and achieves an average 3.8x higher performance than ABFT in ViTs.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 17 references that are in the map. First posted on arXiv 3 Aug 2026.

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10 of 17 references.

References · 10

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Efficient Transformers: A Surveycited by 784
  3. 2023A Systematic Literature Review on Hardware Reliability Assessment Methods for Deep Neural Networkscited by 23
  4. 2020FT-CNN: Algorithm-Based Fault Tolerance for Convolutional Neural Networkscited by 21
  5. 2024ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Trainingcited by 11
  6. 2025FT-Transformer: Resilient and Reliable Transformer with End-to-End Fault Tolerant Attentioncited by 8
  7. 2023ALBERTA: ALgorithm-Based Error Resilience in Transformer Architecturescited by 3
  8. 2025Custom Algorithm-based Fault Tolerance for Attention Layers in Transformerscited by 2
  9. 2026Effective and Memory-Efficient Alternatives to ECC for Reliable Large-Scale DNNscited by 2
  10. 2026In Transformer We Trust? A Perspective on Transformer Architecture Failure Modescited by 1

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