4 papers
SAGE-PINN: A Singularity-free Axisymmetric Geometry-Encoded Physics-Informed Neural Network for Axisymmetric Multiphysics Flow in Cylindrical Coordinates
Raj Maurya, Joyprakash Akhuli, Doyel Pandey
Physics-informed neural networks (PINNs) provide a mesh-free framework for multiphysics modeling, yet fluid flow in axisymmetric cylindrical coordinates remains largely unexplored…
Unveiling the Merits and Defects of LLMs in Automatic Review Generation for Scientific Papers
Ruochi Li, Haoxuan Zhang, Edward Gehringer +3
The surge in scientific submissions has placed increasing strain on the traditional peer-review process, prompting the exploration of large language models (LLMs) for automated rev…
Human-in-the-Loop Systems for Adaptive Learning Using Generative AI
Bhavishya Tarun, Haoze Du, Dinesh Kannan +1
A Human-in-the-Loop (HITL) approach leverages generative AI to enhance personalized learning by directly integrating student feedback into AI-generated solutions. Students critique…
Objective Metrics for Evaluating Large Language Models Using External Data Sources
Haoze Du, Richard Li, Edward Gehringer
Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a frame…