5 papers
Knowledge Rumination for Client Utility Evaluation in Heterogeneous Federated Learning
Xiaorui Jiang, Yu Gao, Hengwei Xu +3
Federated Learning (FL) allows several clients to cooperatively train machine learning models without disclosing the raw data. In practical applications, asynchronous FL (AFL) can…
Noise-NeRF: Hide Information in Neural Radiance Fields using Trainable Noise
Qinglong Huang, Haoran Li, Yong Liao +2
Neural Radiance Field (NeRF) has been proposed as an innovative advancement in 3D reconstruction techniques. However, little research has been conducted on the issues of informatio…
3D-GOI: 3D GAN Omni-Inversion for Multifaceted and Multi-object Editing
Haoran Li, Long Ma, Haolin Shi +4
The current GAN inversion methods typically can only edit the appearance and shape of a single object and background while overlooking spatial information. In this work, we propose…
DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Sampling
Haoran Li, Haolin Shi, Wenli Zhang +5
Text-to-3D scene generation holds immense potential for the gaming, film, and architecture sectors. Despite significant progress, existing methods struggle with maintaining high qu…
A + B: A General Generator-Reader Framework for Optimizing LLMs to Unleash Synergy Potential
Wei Tang, Yixin Cao, Jiahao Ying +4
Retrieval-Augmented Generation (RAG) is an effective solution to supplement necessary knowledge to large language models (LLMs). Targeting its bottleneck of retriever performance,…