English

Agree on the Model, Verify the Inference: GKR Protocols for HND-Based Transformer Inference

Machine Learning 2026-07-23 v1 Cryptography and Security

Abstract

Outsourced Transformer inference exposes clients to model substitution and incomplete execution, while direct replay removes the computational benefit of delegation. We present GKR-HND, a registered-model protocol for verifying the polynomial backbone of Homomorphic--Nonhomomorphic Decomposition Transformers. The retained verifier checks the GKR transcript and registered-weight openings, but delegates expensive public evaluations to an assigned computation worker. Assuming an honest retained verifier and prover--worker non-collusion, the verifier accepts only when the worker's signed, request-bound response agrees with the proof claims. Experiments with pretrained HND models validate the proof path and the delegated public computation without dense-matrix replay.

Cite

@article{arxiv.2607.21162,
  title  = {Agree on the Model, Verify the Inference: GKR Protocols for HND-Based Transformer Inference},
  author = {Xiaolong Liang and Juanjuan Li and Rui Qin and Yisheng Lv},
  journal= {arXiv preprint arXiv:2607.21162},
  year   = {2026}
}

Comments

24 pages, including 4 pages of supporting information; 2 figures