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Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics We show that text-trained foundation models can accurately extrapolate spatiotemporal dynamics from discretized partial differential equation (PDE) solutions without fine-tuning or natural language prompting
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics Inspired by the successes of pre-trained language foundation models, we pose a question about whether these models can also be adapted to solve time-series forecasting
Code associated with the paper Text-Trained LLMs Can Zero-Shot . . . This repository contains the code to reproduce all data and figures from “Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics” by Jiajun Bao, Nicolas Boullé, Toni J B Liu, Raphaël Sarfati, and Christopher J Earls The code will be released publicly upon publication of this work
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics We show that text-trained foundation models can accurately extrapolate spatiotemporal dynamics from discretized partial differential equation (PDE) solutions without fine-tuning or natural language prompting
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics The paper investigates the capability of large language models (LLMs) to perform zero-shot extrapolation of dynamics from discretized partial differential equations (PDEs) without requiring fine-tuning or natural language prompting
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics We show that text-trained foundation models can accurately extrapolate spatiotemporal dynamics from discretized partial differential equation (PDE) so- lutions without fine-tuning or natural language prompting
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics | alphaXiv We show that text-trained foundation models can accurately extrapolate spatiotemporal dynamics from discretized partial differential equation (PDE) solutions without fine-tuning or natural language prompting
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics | AI Research . . . Overview • Large language models can now predict complex physical system dynamics without specific training • Researchers demonstrated zero-shot extrapolation of partial differential equations (PDEs) • Models can learn underlying mathematical principles from text-based training