11 citations · 39 across the 32 of their papers we have counts for
10 papers · 1 filter
Pushing Rendering Boundaries: Hard Gaussian Splatting
Qingshan Xu, Jiequan Cui, Xuanyu Yi +4
3D Gaussian Splatting (3DGS) has demonstrated impressive Novel View Synthesis (NVS) results in a real-time rendering manner. During training, it relies heavily on the average magni…
Dockformer: A transformer-based molecular docking paradigm for large-scale virtual screening
Zhangfan Yang, Junkai Ji, Shan He +5
Molecular docking is a crucial step in drug development, which enables the virtual screening of compound libraries to identify potential ligands that target proteins of interest. H…
Generative AI as a Tool or Leader? Exploring AI-Augmented Thinking in Student Programming Tasks
Tianlong Zhong, Gaoxia Zhu, Kang You Lim +1
The increasing use of Generative Artificial Intelligence (GAI) tools in education highlights the need to understand their influence on individuals' thinking processes and agency. T…
Video Set Distillation: Information Diversification and Temporal Densification
Yinjie Zhao, Heng Zhao, Bihan Wen +2
The rapid development of AI models has led to a growing emphasis on enhancing their capabilities for complex input data such as videos. While large-scale video datasets have been i…
Towards Harmless Rawlsian Fairness Regardless of Demographic Prior
Xuanqian Wang, Jing Li, Ivor W. Tsang +1
Due to privacy and security concerns, recent advancements in group fairness advocate for model training regardless of demographic information. However, most methods still require p…
Few-shot NeRF by Adaptive Rendering Loss Regularization
Qingshan Xu, Xuanyu Yi, Jianyao Xu +3
Novel view synthesis with sparse inputs poses great challenges to Neural Radiance Field (NeRF). Recent works demonstrate that the frequency regularization of Positional Encoding (P…
ExpertFlow: Efficient Mixture-of-Experts Inference via Predictive Expert Caching and Token Scheduling
Xin He, Shunkang Zhang, Kaijie Tang +8
Sparse Mixture-of-Experts (MoE) models can outperform dense large language models at similar computation by activating only a small set of experts per token. However, stacking many…
Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model
Melvin Wong, Thiago Rios, Stefan Menzel +1
Engineering design optimization requires an efficient combination of a 3D shape representation, an optimization algorithm, and a design performance evaluation method, which is ofte…
Covariance-Adaptive Sequential Black-box Optimization for Diffusion Targeted Generation
Yueming Lyu, Kim Yong Tan, Yew Soon Ong +1
Diffusion models have demonstrated great potential in generating high-quality content for images, natural language, protein domains, etc. However, how to perform user-preferred tar…
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…