Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundamentally addressing the problems of excessive parameters and cold starts. However, the most common tokenizer, RQ-VAE, suffers from low decoding efficiency due to the inhere...
Nian Li, Chonggang Song, Jingtao Ding et al.· 0 citations
This work proposes Real-time Adaptive Physics-Informed Diffusion (RAPID), a unified framework explicitly designed to balance high-fidelity generation with strict real-time constraints, and establishes a new state-of-the-art balance between fidelity and safety.
Zihan Yu, Huandong Wang, Jing-Tao Ding et al.· Proceedings of the 32nd ACM...· 0 citations
The Act2Intention framework is proposed, which builds an active mobile agent by integrating understanding, predicting user intentions, and executing decisions, and establishes a standardized platform for developing and evaluating proactive agents and consequently paves the way for research on intention-driven human-com...
Xiaokai Yan, Jing-Tao Ding, Yong Li et al.· Proceedings of the ACM on In...· 0 citations
Generating realistic and diverse pedestrian background flows is critical for numerous downstream applications, ranging from the training and validation of autonomous driving systems to the simulation of mobile communication networks. While recent diffusion-based models achieve state-of-the-art accuracy, they suffer fro...
Zihan Yu, Huandong Wang, Jingtao Ding et al.· Proceedings of the 32nd ACM...· 0 citations
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