28 citations · 28 across the 1 of their papers we have counts for
7 papers
Prompt Evolution for Generative AI: A Classifier-Guided Approach
Melvin Wong, Yew-Soon Ong, Abhishek Gupta +2
Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with generative AI. However, such models often fa…
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…
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…
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…
LLM-to-Phy3D: Physically Conform Online 3D Object Generation with LLMs
Melvin Wong, Yueming Lyu, Thiago Rios +2
The emergence of generative artificial intelligence (GenAI) and large language models (LLMs) has revolutionized the landscape of digital content creation in different modalities. H…