MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation.

Yi Xu|Moyu Zhang|Chenxuan Li|Zhihao Liao|Haibo Xing|Hao Deng|Jinxin Hu|Yu Zhang|Xiaoyi Zeng|Jing Zhang


Anthology ID:DBLP:conf/wsdm/XuZL0X0H0Z026
Volume:Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026
Year:2026
Venue:Web Search and Data Mining (WSDM)
Publisher:ACM
Pages:788-797
URL:https://doi.org/10.1145/3773966.3777923
DOI:https://doi.org/10.1145/3773966.3777923
DBLP:conf/wsdm/XuZL0X0H0Z026
BibTeX:
@inproceedings{xu-2026-mmq, author = {Yi Xu and Moyu Zhang and Chenxuan Li and Zhihao Liao and Haibo Xing and Hao Deng and Jinxin Hu and Yu Zhang and Xiaoyi Zeng and Jing Zhang}, title = {{MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation}}, booktitle = {{Proceedings of the Nineteenth ACM International Conference on Web Search and Data Mining, WSDM 2026, Boise, ID, USA, February 22-26, 2026}}, pages = {788--797}, publisher = {ACM}, year = {2026}, url = {https://doi.org/10.1145/3773966.3777923}, doi = {https://doi.org/10.1145/3773966.3777923} }