2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.IR2025
Token-Controlled Re-ranking for Sequential Recommendation via LLMs
Wenxi Dai, Wujiang Xu, Pinhuan Wang +1
The widespread adoption of Large Language Models (LLMs) as re-rankers is shifting recommender systems towards a user-centric paradigm. However, a significant gap remains: current r…
cs.IR2025
REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking
Pinhuan Wang, Zhiqiu Xia, Chunhua Liao +2
Large Language Models (LLMs) have shown strong capabilities in document re-ranking, a key component in modern Information Retrieval (IR) systems. However, existing LLM-based approa…
cs.DC2025★ 2 cited
Bingo: Radix-based Bias Factorization for Random Walk on Dynamic Graphs
Pinhuan Wang, Chengying Huan, Zhibin Wang +3
Random walks are a primary means for extracting information from large-scale graphs. While most real-world graphs are inherently dynamic, state-of-the-art random walk engines faile…