Every (n-2)-dimensional subspace of R^n (n even) contains a nonzero vector with largest-to-second-largest absolute entry ratio at least n/2 - 1, and the general lower bound on single-error detection height is tight when n-k divides k.
58 Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré
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The paper constructs hash-linked evidence graphs that bind hardware measurement quantities to their verification records, enabling offline auditing with probabilistic matrix checks and security measures against probe attacks on GPUs.
DEFault++ applies hierarchical learning with a Fault Propagation Graph to detect, localize, and diagnose faults in transformers, improving F1 to 0.826-0.909 and developer repair accuracy from 57.1% to 83.3% on a new benchmark of 5,556 mutation-tested runs.
citing papers explorer
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Tight Lower Bounds on The Single-Error Detection Threshold for Analog Error-Correcting Codes
Every (n-2)-dimensional subspace of R^n (n even) contains a nonzero vector with largest-to-second-largest absolute entry ratio at least n/2 - 1, and the general lower bound on single-error detection height is tight when n-k divides k.
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Self-Verifying Measurement Records: Hash-Linked Evidence Graphs for Hardware Benchmarking
The paper constructs hash-linked evidence graphs that bind hardware measurement quantities to their verification records, enabling offline auditing with probabilistic matrix checks and security measures against probe attacks on GPUs.
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Hierarchical Fault Detection and Diagnosis for Transformer Architectures
DEFault++ applies hierarchical learning with a Fault Propagation Graph to detect, localize, and diagnose faults in transformers, improving F1 to 0.826-0.909 and developer repair accuracy from 57.1% to 83.3% on a new benchmark of 5,556 mutation-tested runs.