1 citations · 1 across the 4 of their papers we have counts for
5 papers
OATS: Online Data Augmentation for Time Series Foundation Models
Junwei Deng, Chang Xu, Jiaqi W. Ma +5
Time Series Foundation Models (TSFMs) are a powerful paradigm for time series analysis and are often enhanced by synthetic data augmentation to improve the training data quality. E…
Diff-MN: Diffusion Parameterized MoE-NCDE for Continuous Time Series Generation with Irregular Observations
Xu Zhang, Junwei Deng, Chang Xu +2
Time series generation (TSG) is widely used across domains, yet most existing methods assume regular sampling and fixed output resolutions. These assumptions are often violated in…
CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks
Xu Zhang, Hao Li, Zhichao Lu
Multimodal Large Language Models (MLLMs) achieve strong reasoning and perception capabilities but are increasingly vulnerable to jailbreak attacks. While existing work focuses on e…
Negative Pre-aware for Noisy Cross-modal Matching
Xu Zhang, Hao Li, Mang Ye
Cross-modal noise-robust learning is a challenging task since noisy correspondence is hard to recognize and rectify. Due to the cumulative and unavoidable negative impact of unreso…
Image-text Retrieval via Preserving Main Semantics of Vision
Xu Zhang, Xinzheng Niu, Philippe Fournier-Viger +1
Image-text retrieval is one of the major tasks of cross-modal retrieval. Several approaches for this task map images and texts into a common space to create correspondences between…