3 papers
cs.IR2025
Massive Memorization with Hundreds of Trillions of Parameters for Sequential Transducer Generative Recommenders
Zhimin Chen, Chenyu Zhao, Ka Chun Mo +7
Modern large-scale recommendation systems rely heavily on user interaction history sequences to enhance the model performance. The advent of large language models and sequential mo…
cs.IR2025
LIME: Link-based User-item Interaction Modeling with Decoupled XOR Attention for Efficient Test Time Scaling
Yunjiang Jiang, Ayush Agarwal, Yang Liu +3
Scaling large recommendation systems requires advancing three major frontiers: processing longer user histories, expanding candidate sets, and increasing model capacity. While prom…
math.PR2010
On Number of Turns in Reduced Random Lattice Paths
Yunjiang Jiang, Weijun Xu
We consider the tree-reduced path of symmetric random walk on $\ZZ^{d}$. It is interesting to ask about the number of turns in the reduced path after steps. This question…