GEARS (Generative Engine for Agentic Ranking Systems), a framework that reframes ranking optimization as an autonomous discovery process within a programmable experimentation environment, and incorporates validation hooks to enforce statistical robustness and filter out brittle policies that overfit short-term signals.
Longfei Yun, Yihang Wu, Haoran Liu et al.· arXiv.org· 2 citations
CCTU, a benchmark for evaluating LLM tool use under complex constraints, is introduced and nine state-of-the-art LLMs are evaluated in both thinking and non-thinking modes, showing that models violate constraints in over 50% of cases.
Junjie Ye, Guoqiang Zhang, Wen-Jie Fu et al.· arXiv.org· 8 citations
SPIEval is introduced, a human-curated benchmark grounded in five cognitive capabilities that exposes fundamental limitations of current LLM-based mobile assistants and motivates future research in this direction.
Junjie Ye, Zhuohui Sheng, Shao-Hua Liu et al.· 0 citations
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