4 citations · 6 across the 8 of their papers we have counts for
8 papers
Learning Graphs through Continuous Information Entropy Fields
Hui Cong, Bo Sun, Ziheng Jiao +1
Graph theory is inherently descriptive, capturing what relationships exist but not why they arise, because it treats edges as primitive constructs. This paper proposes a new explan…
GRPO-RM: Fine-Tuning Representation Models via GRPO-Driven Reinforcement Learning
Yanchen Xu, Ziheng Jiao, Hongyuan Zhang +1
The Group Relative Policy Optimization (GRPO), a reinforcement learning method used to fine-tune large language models (LLMs), has proved its effectiveness in practical application…
Explore How to Inject Beneficial Noise in MLLMs
Ruishu Zhu, Sida Huang, Ziheng Jiao +1
Multimodal Large Language Models (MLLMs) have played an increasingly important role in multimodal intelligence. However, the existing fine-tuning methods often ignore cross-modal h…
Never compromise with vulnerabilities: a comprehensive survey on AI governance
Yuchu Jiang, Jian Zhao, Yuchen Yuan +62
The rapid advancement of AI has expanded its capabilities across domains, yet introduced critical technical vulnerabilities, such as algorithmic bias and adversarial sensitivity, t…
CNN2GNN: How to Bridge CNN with GNN
Ziheng Jiao, Hongyuan Zhang, Xuelong Li
Although the convolutional neural network (CNN) has achieved excellent performance in vision tasks by extracting the intra-sample representation, it will take a higher training exp…
Deep Manifold Learning with Graph Mining
Xuelong Li, Ziheng Jiao, Hongyuan Zhang +1
Admittedly, Graph Convolution Network (GCN) has achieved excellent results on graph datasets such as social networks, citation networks, etc. However, softmax used as the decision…
Deep Contrastive Graph Representation via Adaptive Homotopy Learning
Rui Zhang, Chengjun Lu, Ziheng Jiao +1
Homotopy model is an excellent tool exploited by diverse research works in the field of machine learning. However, its flexibility is limited due to lack of adaptiveness, i.e., man…
Non-Gradient Manifold Neural Network
Rui Zhang, Ziheng Jiao, Hongyuan Zhang +1
Deep neural network (DNN) generally takes thousands of iterations to optimize via gradient descent and thus has a slow convergence. In addition, softmax, as a decision layer, may i…