3 papers
cs.GT2026
Repeated-Game Security for Restaking-Based Verifiable Inference
Zhenhang Shang, Yingzhe Yu, Kani Chen
Restaking-based protocols enable verifiable LLM inference without the high proving cost of zkML or the hardware trust assumptions of TEEs. Their security is commonly justified by a…
cs.CR2026
Fine-Tuning Integrity for Modern Neural Networks: Structured Drift Proofs via Norm, Rank, and Sparsity Certificates
Zhenhang Shang, Yingzhe Yu, Kani Chen
Fine-tuning is the dominant paradigm for adapting large machine learning models, yet current deployment pipelines provide no way to verify how a released model was updated. In part…
cs.CR2026
RegGuard: Legitimacy and Fairness Enforcement for Optimistic Rollups
Zhenhang Shang, Yingzhe Yu, Kani Chen
Optimistic rollups provide scalable smart-contract execution but remain unsuitable for regulated financial applications due to three structural gaps: semantic legitimacy, cross-lay…