1 citations · 2 across the 5 of their papers we have counts for
6 papers
Finding Sets of Pareto Sets in Real-World Scenarios -- A Multitask Multiobjective Perspective
Jiao Liu, Yew Soon Ong, Melvin Wong
Recently, evolutionary multitasking has been employed to generate a ``set of Pareto sets" (SOS) for machine learning models, addressing diverse task settings across heterogeneous e…
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…
A Plug-and-Play Multi-Criteria Guidance for Diverse In-Betweening Human Motion Generation
Hua Yu, Jiao Liu, Xu Gui +3
In-betweening human motion generation aims to synthesize intermediate motions that transition between user-specified keyframes. In addition to maintaining smooth transitions, a cru…
LLM2TEA: An Agentic AI Designer for Discovery with Generative Evolutionary Multitasking
Melvin Wong, Jiao Liu, Thiago Rios +2
This paper presents LLM2TEA, a Large Language Model (LLM) driven MultiTask Evolutionary Algorithm, representing the first agentic AI designer of its kind operating with generative…
Precise-Physics Driven Text-to-3D Generation
Qingshan Xu, Jiao Liu, Melvin Wong +2
Text-to-3D generation has shown great promise in generating novel 3D content based on given text prompts. However, existing generative methods mostly focus on geometric or visual p…
Bayesian Inverse Transfer in Evolutionary Multiobjective Optimization
Jiao Liu, Abhishek Gupta, Yew-Soon Ong
Transfer optimization enables data-efficient optimization of a target task by leveraging experiential priors from related source tasks. This is especially useful in multiobjective…