32 papers
From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents
Zijie Zhuang, Changxin Lao, Pengbo Xu +13
Research agents increasingly conduct multi-round machine-learning experiments in industrial recommendation settings and retain the resulting trajectories to guide later decisions.…
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
Xiaoshuai Song, Liancheng Zhang, Kangzhi Zhao +8
Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-wide search and research-orien…
UniFormer: Efficient and Unified Model-Centric Scaling for Industrial Recommendation
Bo Chen, Jinlong Jiao, Tijian Hu +12
Recently, substantial progress has been made in industrial recommendation through component-centric model scaling, where individual components such as behavior modeling, feature in…
Recommendation as Generation: Unifying Personalized Video Generation and Recommendation at Industrial Scale
Yanhua Cheng, Bo Wang, Haotian Zhang +17
Traditional short-video recommendation systems match user interest to a fixed pool of pre-produced videos, which limits their ability to capture fine-grained and dynamic preference…
DADF: A Distribution-Aware Debiasing Framework for Watch-Time Regression in Recommender Systems
Yiqing Yang, Xinlong Zhao, Zhao Liu +4
Watch-time predictors in short-video recommender systems can be approximately calibrated by their own scores while still overestimating short observations and underestimating long…
ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling
Tianbao Ma, Chang Xi, Yichuan Zou +7
Accurate user modeling often depends on rich interaction histories, which are unavailable for billions of low-activity users. Large Language Models (LLMs) can infer latent user sta…