12 citations · 13 across the 7 of their papers we have counts for
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cs.IR2026
Generative Retrieval for E-commerce: Jointly Learning Embedding and Codebook with Same Product Cluster
Songtao Fang, Zihao Xu, Shaowei Wei +2
With the development of large language models (LLMs), generative retrieval is becoming increasingly important in e-commerce scenarios. Current mainstream approaches typically use a…
cs.IR2026
Probabilistic Residual Learning for Online Recommendations
Wenyuan Wang, Yusong Zhao, Zihao Xu +11
Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items. As a result, these systems often suffe…
cs.CL2026
Compressing Sequences in the Latent Embedding Space: -Token Merging for Large Language Models
Zihao Xu, John Harvill, Ziwei Fan +3
Large Language Models (LLMs) incur significant computational and memory costs when processing long prompts, as full self-attention scales quadratically with input length. Token com…