Papers by Chengxi She

    1 papers
    Crossroads of Optimization under Uncertainty: How to Choose the Optimal Model (2026.findings-acl)

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    Challenge: Existing approaches to Optimization under Uncertainty (OuU) have inherent limitations and advantages.
    Approach: They propose a framework that automates the modeling and solving of six types of uncertainty models and generates mapping pairs to explore the potential relationship between optimization problems and optimal models.
    Outcome: The proposed framework achieves superior performance even on specific model types, with correlation analysis showing that data scale and specific scenario significantly influence model selection.

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