Author

Chang-Ho Shin

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#artificial intelligence Preprint Oct 2026

MiniCorp: The Last Mile of the AI Agent Firm

The last mile toward enterprise AGI is a company that runs itself. Training and adapting such agents require longitudinal enterprise data, which remain scarce, costly to acquire, and often restricted by privacy constraints. Historical archives are also frequently incomplete and record only what actually happened. They...

Jing-Ying Zeng, Zhen-Wei Dai, Jin-Ning Li et al. · 0 citations

#artificial intelligence Feb 2026

CARE: Confounder-Aware Aggregation for Reliable LLM Evaluation

CARE is introduced, a confounder-aware aggregation framework that explicitly models LLM judge scores as arising from both a latent true-quality signal and shared confounding factors and separates quality from confounders without access to ground-truth labels.

Jitian Zhao, Chang-Ho Shin, Tzu-Heng Huang et al. · arXiv.org · 11 citations · ⚡2