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cs.LG2025
PDE Solvers Should Be Local: Fast, Stable Rollouts with Learned Local Stencils
Chun-Wun Cheng, Bin Dong, Carola-Bibiane Schönlieb +1
Neural operator models for solving partial differential equations (PDEs) often rely on global mixing mechanisms-such as spectral convolutions or attention-which tend to oversmooth…
cs.LG2025
InverseScope: Scalable Activation Inversion for Interpreting Large Language Models
Yifan Luo, Zhennan Zhou, Bin Dong
Understanding the internal representations of large language models (LLMs) is a central challenge in interpretability research. Existing feature interpretability methods often rely…
cs.LG2023
Prompt Engineering Through the Lens of Optimal Control
Yifan Luo, Yiming Tang, Chengfeng Shen +2
Prompt Engineering (PE) has emerged as a critical technique for guiding Large Language Models (LLMs) in solving intricate tasks. Its importance is highlighted by its potential to s…