Author

Xin-Yu He

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#machine learning Preprint Sep 2026

Harnessing Image Question Dependence for Better VLM Test-time Reinforcement Learning

The proposed TTIQ, a test-time reinforcement learning framework that harnesses image-question dependence for better vlm adaptation, combines image and question dependence with calibrated confidence to construct a response-level reward that favors jointly grounded responses.

Xinrui He, Ting-Wei Li, Jun-Ting Wang et al. · 0 citations

Preprint Aug 2026

Operationally Feasible Synthetic Power-Grid Scenarios via Learning the AC-Operable Joint Distribution

A feasibility-aware distribution-learning framework that learns the AC-operable joint distribution of network topology, branch electrical parameters, and time-varying load profiles and significantly improves operational feasibility and contingency robustness while maintaining strong statistical fidelity and eliminating...

Chen-Han Xiao, Xin-Yu He, Hao-Ran Li et al. · 1 citation