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Lyumanshan Ye

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#artificial intelligence Review Sep 2026

How Far Do Persona Effects Generalize in Language Models?

A separate survey comparison finds that selecting the more responsive checkpoint can worsen human fit; responsiveness is confounded with training status, and temperature calibration largely removes this cost but not errors in group ordering.

Yu-Fan Zhou, Yuxuan Liu, En-Ze Ma et al. · 0 citations
#artificial intelligence Preprint Sep 2026

MOPD-Router: Rethinking Teacher Routing in Multi-Teacher On-Policy Distillation

This work proposes ExpertAlign, a framework that routes supervision over the full teacher pool at each token, without domain labels or training a separate routing model, and demonstrates token-level routing can exploit cross-domain complementary supervision, and reduce exclusive reliance on prompt-level domain assignme...

Tian-Ze Xu, Yan-Zhao Zheng, Zhen-Tao Zhang et al. · 1 citation
#artificial intelligence Preprint Sep 2026

ERPBench: Evaluating LLM Agents for Enterprise Decision-Making Across Competitive Market Ecologies

ERPBench is introduced, an execution-instrumented benchmark for enterprise decision agents in a six-round Enterprise Resource Planning simulation with coupled pricing, production, procurement, inventory, finance, and shared-market competition.

Xin-Ran Zhang, Peng-Rui Lu, Lyumanshan Ye et al. · 1 citation

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