Video generation is shifting from end-to-end synthesis toward agentic generation, where planning, tool use, and feedback enable coherent, controllable multi-shot videos. In parallel, video world model
Agent harnesses integrate video generation and world models to enable planning, tool use, and recursive self-improvement for autonomous multi-shot video production.
Video generation is shifting from end-to-end synthesis toward agentic generation, where planning, tool use, and feedback enable coherent, controllable multi-shot videos. In parallel, video world models provide action-conditioned observations and predicted futures, serving as interactive environments for agents. We study their intersection through the agent harness: an executable runtime that constructs context, exposes tools, maintains state, routes feedback, and manages budgets around video models. This report examines three directions. First, agentic video generation, where harnesses coordinate scripting, shot planning, asset management, production, and editing, alongside the evaluation…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Video Generation Meets Agent Harness: Agentic Video Generation, Agentic World Modeling and Recursive Self-Improvement was first seen on Hugging Face · Daily papers on Nov 3, 2026. Since then it has appeared in 13 checks on 2 different days. Its best position was #2 of 30, reached on Nov 3, 11:28 UTC. It dropped off the list after Nov 4, 03:28 UTC.
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Not at the moment. It was last on the list on Nov 4, 03:28 UTC, after 2 days of trending.
#2 on Hugging Face · Daily papers, on Nov 3, 11:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 3, 2026 and has been on the list on 2 days (13 checks) since.