Social World Model for Lifelong Social Intelligence
Social intelligence is a core competency for language agents, yet current research primarily focuses on static capability evaluation rather than how these skills are continuously shaped and accumulated. This gap calls for a shift toward sustainable learning paradigms. Currently, two methodological pain points exist: social interaction trajectories lack unified structured representations to form iterable learning signals, and capability improvement and retention are typically studied in isolation, hindering the assessment of continuous evolution. To bridge this gap, we propose the Social World Model. We decompose social interaction into five dimensions (scene setting, observation, mental s...
| Authors | Yu Luo |
|---|---|
| Primary category | cs.AI |
| Published | 19 June 2026 |
| Last updated at source | 19 June 2026 |
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