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Ye Jin

COLM 2026智能体与工具多模态对齐与偏好
新星分贡献者
22
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核心/参与5
方向广度6
合作网络3
0 一作 · 1 篇 · COLM 2026

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2026 顶会论文

1
作者位次 #5/16COLM 2026Poster· Poster Session 6· Imperial Ballroom· #17

Co-Director: Agentic Generative Video Storytelling

Yale Song · Yiwen Song · Nick Losier · Nathan Hodson · Ye Jin · Rhyard Zhu · Yan Xu · Daniel Vlasic · Carina Claassen · Jasmine Leon · Khanh G. LeViet · Zack Chomyn · Joe Timmons · Brett Slatkin · Scott Penberthy · Tomas Pfister

We propose an agentic video storytelling framework that formulates generation as a global optimization problem, utilizing Multi-Armed Bandits to navigate a creative latent space and produce high-fidelity, cohesive narratives.

摘要

While diffusion models generate high-fidelity video clips, transforming them into coherent, long-form storytelling engines remains challenging. Current agentic pipelines automate this via chained modules but suffer from semantic drift and cascading failures due to independent, handcrafted prompting. We present Co-Director, a hierarchical multi-agent framework formalizing video storytelling as a global optimization problem. To ensure semantic coherence, we introduce hierarchical parameterization: a multi-armed bandit globally steers creative directions, while local, agent-level self-refinement loops target specific modalities (e.g., storylines, keyframes) to collectively enforce global narrative and visual consistency while mitigating identity drift. This balances the exploration of novel narrative strategies with the exploitation of effective creative configurations. For evaluation, we introduce GenAD-Bench, a 400-scenario dataset of fictional products for personalized advertising. Experiments demonstrate that \moniker significantly outperforms state-of-the-art baselines, offering a principled approach that seamlessly generalizes to broader cinematic narratives. Project webpage: https://co-director-agent.github.io/

智能体与工具多模态对齐与偏好Video generationvideo storytellingmulti-agent systemsOpenReview

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