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cs.IR2026
CoRe: A Continuously Reward-Finetuned LLM Query Rewriter for Multi-Stage Context-Aware Relevance in Web-Scale Video Search
Yilin Wen, Rong Yang, Xiaojia Chang +11
LLM-based query rewriters in production face a tension: the training reward must reflect how the rewrite is consumed by the production ranker, yet the training procedure must be ch…
cs.IR2026
Farewell to Item IDs: Unlocking the Scaling Potential of Large Ranking Models via Semantic Tokens
Zhen Zhao, Tong Zhang, Jie Xu +5
Recent studies on scaling up ranking models have achieved substantial improvement for recommendation systems and search engines. However, most large-scale ranking systems rely on i…