SOURCE-LINKED INTELLIGENCE

SocialBuddy: Tailoring Search Agent for Social Scenarios

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

In the era of digital social interaction, searching friends' posts from massive social streams has become a fundamental user need. However, while modern agentic search frameworks have achieved remarkable success in conventional retrieval tasks, they break down when confronted with heterogeneous user queries and multi-dimensional social feeds, resulting in severe performance degradation in complex social search. To bridge this gap, we introduce SocialBuddy, the first agentic search framework tailored for social scenarios. Specifically, we construct SocialEnv, the first large-scale simulated env

Read original source ↗ Open in workspace

recordType

paper

region

Global