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#machine learning Preprint Sep 2026

KuaFu: Compressing Long User Behavior into Understanding at Billion Scale

Conversational agents, generative recommenders, and personalized advertising all rest on one capability: understanding each user from raw behavior. Prevailing industrial practice is task-specific: for each task, a relevant subsequence is extracted from the full history and a dedicated model trained on it. In production...

Jia-Hao Hui, Lin Zhu, Yi-Sheng Hu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

WFM: Wiki Foundation Model for Complex Agentic Reasoning

Real-world agents fundamentally require persistent non-parametric knowledge for dynamic reasoning, i.e., long-term memory and retrieval-augmented generation. While graphs have shown reliable advantages in providing structured evidence, the sparse graph representations naturally restrict machine readability and semantic...

Jun-Nan Dong, Lin-Hao Luo, Sen-Lei Zhang et al. · 0 citations

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