Author

Kiwan Maeng

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#artificial intelligence Preprint Oct 2026

Verify Less, Evolve More: Training Idea-Level Critics for Verification-Efficient ML Evolving Agents

As large language models become more powerful, self-evolving agents are able to tackle challenging tasks including AI for machine learning (AI4ML). In AI4ML, while empirical verification is available, it often requires computationally costly model training and evaluation, limiting the speed and scale of agent evolution...

Jiamu Bai, Li-Zhu Zhang, Xin Yu et al. · 0 citations

Preprint Aug 2026

Trusted Hardware Acceleration for Function Secret Sharing

The distributed function accelerator (DFA), a hardware accelerator that targets the dominant primitive in FSS: distributed point function (DPF) generation and evaluation, combines a high-throughput fixed-function engine for AES-based pseudorandom number generation with a lightweight programmable unit for protocol-speci...

Pengzhi Huang, Kiwan Maeng, G. Suh · 0 citations

Preprint Aug 2026

Spectrum-Aware Bounds on Invertibility for Privacy-Enhancing Instance Encoding

A family of new bounds that are tighter, applicable even to fully deterministic encoders, and applicable even to fully deterministic encoders can extend beyond MSE to other norm-based similarity metrics, by properly accounting for the encoder's spectral structure.

Seokjin Hwang, Yu-Ting Li, Kiwan Maeng · 0 citations