Push recommendation in KuaiShou proactively delivers personalized content to nearly one billion users to facilitate their engagement. Recently, generative recommendation has achieved end-to-end user personalization through semantic ID. However, their black- box characteristics make recommendation logics difficult to tr...
*Reinforcement learning (RL)* can induce substantial reasoning capabilities in large language models (LLMs), but how much of this capability transfers across model scales, and how quickly, remains unclear. We study the scaling properties of *on-policy distillation (OPD)* across *weak-to-strong*, *same-base*, and *stron...
Yun-Tai Bao, Qin-Feng Li, Guo-qing Jiang et al.· 0 citations
Industrial search platforms must efficiently retrieve relevant items from billions of candidates while satisfying both query relevance and user preferences. Generative Search (GS) has emerged as a transformative paradigm that reformulates traditional indexing and matching as an autoregressive generation task. However,...
Guo-Liang Zhang, Wei-Fan Wang, Jun-Yao Zhao et al.· Proceedings of the 20th ACM...· 0 citations
Search quality evaluation provides essential supervision and diagnostic signals for the development and iteration of industrial search systems. Although large language models (LLMs) offer a scalable alternative to manual assessment, reliable automatic evaluation remains challenging: users experience search results at t...
Zhong-Xin Huang, Song-Yang Li, Ren-Zhe Zhou et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
