10 papers
AffectSeek: Agentic Affective Understanding in Long Videos under Vague User Queries
Zhen Zhang, Yuhang Yang, Yunxiang Jiang +5
Existing affective understanding studies have mainly focused on recognizing emotions from images, audio signals, or pre-cliped video clips, where the affective evidence is already…
Sparse Shortcuts: Facilitating Efficient Fusion in Multimodal Large Language Models
Jingrui Zhang, Feng Liang, Yong Zhang +3
With the remarkable success of large language models (LLMs) in natural language understanding and generation, multimodal large language models (MLLMs) have rapidly advanced in thei…
Revisiting Cross-Architecture Distillation: Adaptive Dual-Teacher Transfer for Lightweight Video Models
Ying Peng, Hongsen Ye, Changxin Huang +3
Vision Transformers (ViTs) have achieved strong performance in video action recognition, but their high computational cost limits their practicality. Lightweight CNNs are more effi…
Nesterov-Accelerated Robust Federated Learning Over Byzantine Adversaries
Lihan Xu, Yanjie Dong, Gang Wang +3
We investigate robust federated learning, where a group of workers collaboratively train a shared model under the orchestration of a central server in the presence of Byzantine adv…
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
Ke Xing, Yanjie Dong, Xiaoyi Fan +4
Personalized federated learning (PFL) addresses a critical challenge of collaboratively training customized models for clients with heterogeneous and scarce local data. Conventiona…
Emotion Recognition from Skeleton Data: A Comprehensive Survey
Haifeng Lu, Jiuyi Chen, Zhen Zhang +3
Emotion recognition through body movements has emerged as a compelling and privacy-preserving alternative to traditional methods that rely on facial expressions or physiological si…