2 citations · 2 across the 26 of their papers we have counts for
Showing cs.IRShow all
2 papers · 1 filter
cs.IR2026
The Case Against Generation for Retrieval: Discriminative Language Models as Effective Retrievers
Zhe Xu, Prachi Agrawal, Kavosh Asadi +17
Large Language Models (LLMs) have emerged as powerful assets for recommender systems. However, deploying them as generative recommenders or zero-shot rankers at web-scale remains b…
cs.IR2026
Tokenizing Numerical and Embedding Features for LLM RecSys
Zhe Xu, Ankit Peshin, Chiyu Zhang +7
Large language models (LLMs) are increasingly used as backbone architectures for recommender systems because of their strong sequence modeling and representation learning capabilit…