Semantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights
Generative agents are increasingly used to select and narrate video highlights, but they typically operate over unstructured or frame-level representations. Their output is consequently difficult for a viewer to verify and steer toward individual preferences. We present the semantic action graph, a lightweight domain schema that represents a sports match as performer, action, recipient, moment, and state nodes connected by role, temporal, and outcome edges. The schema demonstrates three key properties: 1) connected event sequences, 2) a shared, closed vocabulary, and 3) frame-addressable moments, making it suitable to serve two consumers at once: an agentic pipeline that composes narrated...
| Authors | Tica Lin, Deepak Chandran, Gauri Jagatap et al. |
|---|---|
| Primary category | cs.HC |
| Published | 17 September 2026 |
| Last updated at source | 4 October 2026 |
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