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This paper addresses the computational inefficiency and limited generalization of physics-informed neural networks (PINNs) applied to the electrochemical modeling of lithium-ion batteries, specific…
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This paper addresses the task of Remote Sensing Image Change Captioning (RSICC), which seeks to generate natural language descriptions of changes between bi-temporal remote sensing images
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SimFoundry addresses the costly and labor-intensive challenge of training and evaluating robotic manipulation policies in the real world by introducing a modular, automated system for zero-shot rea…
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This chapter outlines the transformative potential of the Square Kilometre Array (SKA) AA4 configuration for disentangling and characterizing star formation and accretion processes in nearby galaxi…
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StructSplat addresses the challenging problem of generalizable 3D scene reconstruction from uncalibrated, sparse multi-view images without requiring any camera intrinsics or extrinsics
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The paper addresses the practical challenge of enabling automated traceability link recovery (TLR) across interrelated software artifacts such as software architecture documentation (SAD), software…
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This paper addresses the growing bottleneck in scientific peer review arising from the rapid surge of AI-assisted scientific output, particularly in fields like mathematics, theoretical computer sc…
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TUA-Bench is a newly introduced benchmark designed to evaluate the capabilities of large language model-powered agents that operate in terminal.
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This paper addresses a fundamental challenge in astrophysics and Galactic studies — reconstructing full three-dimensional (3D) magnetic field vectors in interstellar space
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This qualitative study investigates the real-world implementation of the Artificial Intelligence Assessment Scale (AIAS), a structured framework designed to guide university assessment reform in re…
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This paper addresses an optimal control problem governed by the convective Brinkman-Forchheimer (CBF) equations defined on a d-dimensional torus, for d = 2 or 3
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This paper addresses the significant gap in understanding the early stages of star and planet formation by focusing on characterizing the physical and chemical properties of young embedded protoste…
