11 citations · 12 across the 15 of their papers we have counts for
22 papers
NeuSpring: Neural Spring Fields for Reconstruction and Simulation of Deformable Objects from Videos
Qingshan Xu, Jiao Liu, Shangshu Yu +6
In this paper, we aim to create physical digital twins of deformable objects under interaction. Existing methods focus more on the physical learning of current state modeling, but…
MazeMate: An LLM-Powered Chatbot to Support Computational Thinking in Gamified Programming Learning
Chenyu Hou, Hua Yu, Gaoxia Zhu +3
Computational Thinking (CT) is a foundational problem-solving skill, and gamified programming environments are a widely adopted approach to cultivating it. While large language mod…
Distributional Multi-objective Black-box Optimization for Diffusion-model Inference-time Multi-Target Generation
Kim Yong Tan, Yueming Lyu, Ivor Tsang +1
Diffusion models have been successful in learning complex data distributions. This capability has driven their application to high-dimensional multi-objective black-box optimizatio…
Evolutionary Computation as Natural Generative AI
Yaxin Shi, Abhishek Gupta, Ying Wu +7
Generative AI (GenAI) has achieved remarkable success across a range of domains, but its capabilities remain constrained to statistical models of finite training sets and learning…
Lang-PINN: From Language to Physics-Informed Neural Networks via a Multi-Agent Framework
Xin He, Liangliang You, Hongduan Tian +3
Physics-informed neural networks (PINNs) provide a powerful approach for solving partial differential equations (PDEs), but constructing a usable PINN remains labor-intensive and e…
EvoSpeak: Large Language Models for Interpretable Genetic Programming-Evolved Heuristics
Meng Xu, Jiao Liu, Yew Soon Ong
Genetic programming (GP) has demonstrated strong effectiveness in evolving tree-structured heuristics for complex optimization problems. Yet, in dynamic and large-scale scenarios,…