AAAI 2025technical0 citations
Preliminary Evaluation of the Test-Time Training Layers in Recommendation System (Student Abstract)
Tianyu Zhan, Zheqi Lv, Shengyu Zhang, Jiwei Li
Abstract
This paper explores the application and effectiveness of TestTime Training (TTT) layers in improving the performance of recommendation systems. We developed a model, TTT4Rec, utilizing TTT-Linear as the feature extraction layer. Our tests across multiple datasets indicate that TTT4Rec, as a base model, performs comparably or even surpasses other baseline models in similar environments.
BibTeX
@article{Zhan_Lv_Zhang_Li_2025, title={Preliminary Evaluation of the Test-Time Training Layers in Recommendation System (Student Abstract)}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/35323}, DOI={10.1609/aaai.v39i28.35323}, abstractNote={This paper explores the application and effectiveness of TestTime Training (TTT) layers in improving the performance of recommendation systems. We developed a model, TTT4Rec, utilizing TTT-Linear as the feature extraction layer. Our tests across multiple datasets indicate that TTT4Rec, as a base model, performs comparably or even surpasses other baseline models in similar environments.}, number={28}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Zhan, Tianyu and Lv, Zheqi and Zhang, Shengyu and Li, Jiwei}, year={2025}, month={Apr.}, pages={29554-29557} }