Producing long-form videos from narration requires interdependent decisions that remain coherent across shots. Existing agentic editors often use multi-stage workflows driven by general models, leavin
WeVisCut is a script-to-video system that trains a compact policy to coordinate video editing tools, recover from failures, and reduce token usage while maintaining quality.
Producing long-form videos from narration requires interdependent decisions that remain coherent across shots. Existing agentic editors often use multi-stage workflows driven by general models, leaving the quality-cost trade-off of compact, task-adapted policies unclear. We address this gap with WeVisCut, a long-form script-to-video system that connects tool execution with policy learning. Its agent harness maintains shared production state so that tool feedback informs subsequent decisions and repairs. Because finished videos do not expose these decisions, our four-stage data pipeline combines editing inversion with verified replay to turn recovered editing intent into executable…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
WeVisCut: The Whole Editing Room in One Agent From Narration to Long-Form Video was first seen on Hugging Face · Daily papers on Oct 30, 2026. Since then it has appeared in 38 checks on 4 different days. Its best position was #12 of 30, reached on Nov 2, 03:28 UTC. It dropped off the list after Nov 2, 05:28 UTC.
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Not at the moment. It was last on the list on Nov 2, 05:28 UTC, after 4 days of trending.
#12 on Hugging Face · Daily papers, on Nov 2, 03:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 30, 2026 and has been on the list on 4 days (38 checks) since.