23 citations · 35 across the 9 of their papers we have counts for
9 papers
LLM Nepotism in Organizational Governance
Shunqi Mao, Wei Guo, Dingxin Zhang +2
Large language models are increasingly used to support organizational decisions from hiring to governance, raising fairness concerns in AI-assisted evaluation. Prior work has focus…
Beyond Random Masking: A Dual-Stream Approach for Rotation-Invariant Point Cloud Masked Autoencoders
Xuanhua Yin, Dingxin Zhang, Yu Feng +3
Existing rotation-invariant point cloud masked autoencoders (MAE) rely on random masking strategies that overlook geometric structure and semantic coherence. Random masking treats…
Reflex First, Reflect Later: Latency-Aware Embodied LLM Agents for Dynamic Response
Yangqing Zheng, Shunqi Mao, Dingxin Zhang +1
Large language models (LLMs) have substantially improved the planning capabilities of embodied agents, enabling their deployment in dynamic and safety-critical environments. Howeve…
HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis
Xuanhua Yin, Dingxin Zhang, Jianhui Yu +1
Self-supervised learning (SSL) has demonstrated remarkable success in 3D point cloud analysis, particularly through masked autoencoders (MAEs). However, existing MAE-based methods…
Stealthy Patch-Wise Backdoor Attack in 3D Point Cloud via Curvature Awareness
Yu Feng, Dingxin Zhang, Runkai Zhao +3
Backdoor attacks pose a severe threat to deep neural networks (DNNs) by implanting hidden backdoors that can be activated with predefined triggers to manipulate model behaviors mal…
MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and Retention
Tianyi Wang, Jianan Fan, Dingxin Zhang +4
Histopathology and transcriptomics are fundamental modalities in oncology, encapsulating the morphological and molecular aspects of the disease. Multi-modal self-supervised learnin…
Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module
Dingxin Zhang, Jianhui Yu, Tengfei Xue +3
Current models for point cloud recognition demonstrate promising performance on synthetic datasets. However, real-world point cloud data inevitably contains noise, impacting model…
PaRot: Patch-Wise Rotation-Invariant Network via Feature Disentanglement and Pose Restoration
Dingxin Zhang, Jianhui Yu, Chaoyi Zhang +1
Recent interest in point cloud analysis has led rapid progress in designing deep learning methods for 3D models. However, state-of-the-art models are not robust to rotations, which…
3D Medical Point Transformer: Introducing Convolution to Attention Networks for Medical Point Cloud Analysis
Jianhui Yu, Chaoyi Zhang, Heng Wang +5
General point clouds have been increasingly investigated for different tasks, and recently Transformer-based networks are proposed for point cloud analysis. However, there are bare…