Author

Naichen Shi

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Preprint Sep 2026

Interpolating Neural Operator (INO): A Data-Free and Efficient Approach for Learning PDE Solution Operators

Neural operators have become a popular approach to approximate the solution operators of parametric partial differential equations (PDEs). However, existing neural operators either require a large amount of simulation data or a long physics-informed training on GPUs, and they cannot tell how accurate an individual pred...

Jia-Chen Guo, Ye Lu, Nai-Chen Shi et al. · 0 citations

#natural language process... Preprint Sep 2026

When the Wrong Key Wins: Understanding and Detecting Hallucinations in LLMs

Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent-key view of inference, where answer selection depends on competition among associations acquired during pretraining. We show that model predictions can be highly sensi...

Xu-Han Tong, Hao-Yue Bai, Da-Wei Zhou et al. · 0 citations

Preprint Aug 2026

Multimodal Alignment Through Joint Kernel Entropic Gromov--Wasserstein Optimal Transport

A structure-preserving alignment framework, joint kernel entropic Gromov--Wasserstein Optimal Transport (JK-EGW), which maps multiple modalities into a common latent space by minimizing a quadratic optimal transport objective and achieves improved multimodal retrieval performance compared to existing alignment baseline...

Y. Wu, Yilun Zhu, Naichen Shi · 0 citations