arXiv:2611.01097v1 Announce Type: new Abstract: Decentralizing large language model (LLM) inference across untrusted Web nodes requires robust verification to ensure computational integrity. Existing activation-based verification and detection mechanisms validate intermediate outputs against reference values, permitting bounded numerical deviations to accommodate benign cross-hardware discrepancies.
The Blind Spots of Detection: Adversarial Perturbation Attacks against Watchdogs in Distributed LLM Inference
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