2 papers
cs.IR2026
RecRM-Bench: Benchmarking Multidimensional Reward Modeling for Agentic Recommender Systems
Wenwen Zeng, Jinhui Zhang, Hao Chen +10
The integration of Large Language Model (LLM) agents is transforming recommender systems from simple query-item matching towards deeply personalized and interactive recommendations…
cs.AI2026
CDRRM: Contrast-Driven Rubric Generation for Reliable and Interpretable Reward Modeling
Dengcan Liu, Fengkai Yang, Xiaohan Wang +7
Reward modeling is essential for aligning Large Language Models(LLMs) with human preferences, yet conventional reward models suffer from poor interpretability and heavy reliance on…