2 citations · 2 across the 6 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.IR2026
MISO: Model-Internal-State-Guided Optimization for Ranking Models
Yongzhe Zhang, Xiaoyu Deng, Yifan He +29
Ranking models are repeatedly refined within established model families, yet the choice of which component to scale, replace, or retire is often guided by expensive trial-and-error…
cs.IR2026
GR2 Technical Report
Yufei Li, Zaiwei Zhang, Mingfu Liang +67
Industrial recommendation systems serve billions of users through a multi-stage funnel -- retrieval, early-stage ranking, and re-ranking -- where the final re-ranking step dispropo…
cs.IR2026
GR2: Generative Reasoning Re-ranker
Mingfu Liang, Yufei Li, Jay Xu +20
Recent studies increasingly explore Large Language Models (LLMs) as a new paradigm for recommendation systems due to their scalability and world knowledge. However, existing work h…