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cs.LG2026
Do Models Read What They Write? Causal Registers in Scratchpad Reasoning
Benjamin Shih, John Winnicki, Eric Darve
A central hope behind process supervision is that models can expose intermediate variables that matter for their later behavior. For this to help with alignment, a scratchpad must…
cs.LG2024
Transformers as Neural Operators for Solutions of Differential Equations with Finite Regularity
Benjamin Shih, Ahmad Peyvan, Zhongqiang Zhang +1
Neural operator learning models have emerged as very effective surrogates in data-driven methods for partial differential equations (PDEs) across different applications from comput…