7 papers
ChromouVQA: Benchmarking Vision-Language Models under Chromatic Camouflaged Images
Yunfei Zhang, Yizhuo He, Yuanxun Shao +5
Vision-Language Models (VLMs) have advanced multimodal understanding, yet still struggle when targets are embedded in cluttered backgrounds requiring figure-ground segregation. To…
A Systematic Study of Model Extraction Attacks on Graph Foundation Models
Haoyan Xu, Ruizhi Qian, Jiate Li +9
Graph machine learning has advanced rapidly in tasks such as link prediction, anomaly detection, and node classification. As models scale up, pretrained graph models have become va…
JEPA-T: Joint-Embedding Predictive Architecture with Text Fusion for Image Generation
Siheng Wan, Zhengtao Yao, Zhengdao Li +9
Modern Text-to-Image (T2I) generation increasingly relies on token-centric architectures that are trained with self-supervision, yet effectively fusing text with visual tokens rema…
OrthAlign: Orthogonal Subspace Decomposition for Non-Interfering Multi-Objective Alignment
Liang Lin, Zhihao Xu, Junhao Dong +10
Large language model (LLM) alignment faces a critical dilemma when addressing multiple human preferences: improvements in one dimension frequently come at the expense of others, cr…
AMMKD: Adaptive Multimodal Multi-teacher Distillation for Lightweight Vision-Language Models
Yuqi Li, Chuanguang Yang, Junhao Dong +6
The success of large-scale visual language pretraining (VLP) models has driven widespread adoption of image-text retrieval tasks. However, their deployment on mobile devices remain…
SRKD: Towards Efficient 3D Point Cloud Segmentation via Structure- and Relation-aware Knowledge Distillation
Yuqi Li, Junhao Dong, Zeyu Dong +3
3D point cloud segmentation faces practical challenges due to the computational complexity and deployment limitations of large-scale transformer-based models. To address this, we p…