Semantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights
Paper recorded by Signals 4 on 2026-09-17 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-17 on arXiv · recorded by Signals 4 on 2026-09-18
Category: cs.AI · 人工智能 · first seen 2026-09-18
Abstract
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, an
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Cite this page: Semantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights: the #11 most recent of 300 cs.AI papers we have recorded (as of 2026-09-17). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/semantic-action-graph-a-shared-representation-for-agent-grounding-and-human-inte.html
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