activity
20242026
collaborators

7 papers

cs.CV2026

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…

cs.CY2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.AI2025

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…

cs.CV2025

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…