4 citations · 7 across the 7 of their papers we have counts for
7 papers
PPC-MT: Parallel Point Cloud Completion with Mamba-Transformer Hybrid Architecture
Jie Li, Shengwei Tian, Long Yu +1
Existing point cloud completion methods struggle to balance high-quality reconstruction with computational efficiency. To address this, we propose PPC-MT, a novel parallel framewor…
Disentangling Fact from Sentiment: A Dynamic Conflict-Consensus Framework for Multimodal Fake News Detection
Weilin Zhou, Zonghao Ying, Rongchen Zhao +7
Prevalent multimodal fake news detection relies on consistency-based fusion, yet this paradigm fundamentally misinterprets critical cross-modal discrepancies as noise, leading to o…
CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor
Zhenhua Xu, Xixiang Zhao, Xubin Yue +3
The widespread deployment of large language models (LLMs) has intensified concerns around intellectual property (IP) protection, as model theft and unauthorized redistribution beco…
Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion
Jie Li, Shengwei Tian, Long Yu +1
The Chamfer Distance (CD) is a cornerstone objective function for point cloud completion, yet its inherent symmetric weighting mechanism limits the quality of the generated results…
AutoLLM-CARD: Towards a Description and Landscape of Large Language Models
Shengwei Tian, Lifeng Han, Goran Nenadic
With the rapid growth of the Natural Language Processing (NLP) field, a vast variety of Large Language Models (LLMs) continue to emerge for diverse NLP tasks. As more papers are pu…
DT-Net: A novel network based on multi-directional integrated convolution and threshold convolution
Hongfeng You, Long Yu, Shengwei Tian +3
Since medical image data sets contain few samples and singular features, lesions are viewed as highly similar to other tissues. The traditional neural network has a limited ability…
A New Multiple Max-pooling Integration Module and Cross Multiscale Deconvolution Network Based on Image Semantic Segmentation
Hongfeng You, Shengwei Tian, Long Yu +3
To better retain the deep features of an image and solve the sparsity problem of the end-to-end segmentation model, we propose a new deep convolutional network model for medical im…