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20242026
most citedMoE-FFD: Mixture of Experts for Generalized and Parameter-Efficient Face Forgery Detection

4 citations · 6 across the 11 of their papers we have counts for

collaborators
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5 papers · 1 filter

cs.CV2025

From Pretrain to Pain: Adversarial Vulnerability of Video Foundation Models Without Task Knowledge

Hui Lu, Yi Yu, Song Xia +5

Large-scale Video Foundation Models (VFMs) has significantly advanced various video-related tasks, either through task-specific models or Multi-modal Large Language Models (MLLMs).…

cs.LG2025

MTL-UE: Learning to Learn Nothing for Multi-Task Learning

Yi Yu, Song Xia, Siyuan Yang +5

Most existing unlearnable strategies focus on preventing unauthorized users from training single-task learning (STL) models with personal data. Nevertheless, the paradigm has recen…

cs.CV2025

Open-set Anomaly Segmentation in Complex Scenarios

Song Xia, Yi Yu, Henghui Ding +4

Precise segmentation of out-of-distribution (OoD) objects, herein referred to as anomalies, is crucial for the reliable deployment of semantic segmentation models in open-set, safe…

cs.CR2025

Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation

Yi Yu, Song Xia, Xun Lin +5

Adversarial examples, characterized by imperceptible perturbations, pose significant threats to deep neural networks by misleading their predictions. A critical aspect of these exa…

cs.LG2025

Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems

Song Xia, Yi Yu, Wenhan Yang +5

By locally encoding raw data into intermediate features, collaborative inference enables end users to leverage powerful deep learning models without exposure of sensitive raw data…