2 citations · 6 across the 11 of their papers we have counts for
11 papers
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,…
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…
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…
2D-Guided 3D Gaussian Segmentation
Kun Lan, Haoran Li, Haolin Shi +4
Recently, 3D Gaussian, as an explicit 3D representation method, has demonstrated strong competitiveness over NeRF (Neural Radiance Fields) in terms of expressing complex scenes and…
FedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion
Wei Tang, Zhiqian Wu, Yixin Cao +2
Knowledge graph completion (KGC) aims to predict missing facts in knowledge graphs (KGs), which is crucial as modern KGs remain largely incomplete. While training KGC models on mul…
User Authentication and Identity Inconsistency Detection via Mouse-trajectory Similarity Measurement
Rui Jin, Yong Liao, Pengyuan Zhou
Completely Automated Public Turing Test To Tell Computers and Humans Apart (CAPTCHA) is a type of challenge-response test widely used in authentication systems. A well-known challe…
AHSecAgg and TSKG: Lightweight Secure Aggregation for Federated Learning Without Compromise
Siqing Zhang, Yong Liao, Pengyuan Zhou
Leveraging federated learning (FL) to enable cross-domain privacy-sensitive data mining represents a vital breakthrough to accomplish privacy-preserving learning. However, attacker…
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…
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…
Detect Depression from Social Networks with Sentiment Knowledge Sharing
Yan Shi, Yao Tian, Chengwei Tong +6
Social network plays an important role in propagating people's viewpoints, emotions, thoughts, and fears. Notably, following lockdown periods during the COVID-19 pandemic, the issu…
How Secure is Your Website? A Comprehensive Investigation on CAPTCHA Providers and Solving Services
Rui Jin, Lin Huang, Jikang Duan +3
Completely Automated Public Turing Test To Tell Computers and Humans Apart (CAPTCHA) has been implemented on many websites to identify between harmful automated bots and legitimate…