OPFL: Optimistic Verification of Federated Learning via Empirical Boundary

arXiv:2609.37011 · cs.CR, cs.AI · Submitted 2026-09-29 · Read on arXiv

cs.CR, cs.AI

Submitted: 2026-09-29

Updated: 2026-09-29

Comments: 15 pages, 3 figures, 9 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

Verification — 56× in this paper · explained in 2 episodes
Aggregation — 29× in this paper · explained in 1 episode
Verifier — 25× in this paper · explained in 2 episodes
Calibration — 19× in this paper · explained in 7 episodes
Federated Learning — 17× in this paper · explained in 14 episodes
Generalization — 11× in this paper · explained in 13 episodes
Adaptation — 2× in this paper · explained in 1 episode
IEEE Symposium on Security and Privacy — 2× in this paper
In Network and Distributed System Security Symposium — 2× in this paper
Robustness — 2× in this paper · explained in 5 episodes
Transformer — 2× in this paper · explained in 2 episodes
Transformer Architecture — 2× in this paper · explained in 2 episodes
Accuracy — 1× in this paper · explained in 1 episode
Adversarial Attacks — 1× in this paper · explained in 1 episode
Amortization — 1× in this paper · explained in 1 episode
Consistency — 1× in this paper · explained in 3 episodes
Core — 1× in this paper · explained in 2 episodes
Domain Adaptation — 1× in this paper · explained in 5 episodes
Federated Learning (FL) — 1× in this paper · explained in 7 episodes
Generative AI — 1× in this paper · explained in 2 episodes
OPFL in PyTorch with Secure Processing Unit — 1× in this paper

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