ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu; Shihao Li; Weihong Lin; Xinlong Chen; Yang Shi; Yujin Han; Yiyang Cai; Yanghao Wang; Ruibin Yuan; Yuanxing Zhang; Pengfei Wan; Wenhan Luo; Yike Guo

arXiv · 2607.14681

ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships

Xinyu Liu·Shihao Li·Weihong Lin·Xinlong Chen·Yang Shi·Yujin Han·Yiyang Cai·Yanghao Wang·Ruibin Yuan·Yuanxing Zhang·Pengfei Wan·Wenhan Luo·Yike Guo

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Abstract

Recent diffusion-based video generation models have made significant progress in multi-reference image-conditioned video editing. However, existing methods still struggle to coordinate information from multiple visual sources accurately. We identify a critical deficiency in existing approaches. Existing editing instructions lack explicit reference relationships, and most multimodal large language models (MLLMs) cannot generate them reliably. To address this problem, we propose ReBind, a systematic framework that introduces semantic instructions with embedded reference tokens as the intermediate representation for multi-reference image-conditioned video editing. Our key insight is embedding reference tokens at semantic positions to eliminate ambiguity and establish precise bindings between visual attributes and their sources. We develop ReBind-Instruct, a specialized MLLM that learns to establish explicit bindings between visual attributes and their reference sources through a two-stage progressive scheme for precise reference relationships. We further develop ReBind-Edit, which enables lightweight adaptation of text-to-video models to coordinate multiple references by binding visual attributes to their designated sources. Extensive experiments demonstrate that ReBind substantially outperforms general-purpose MLLMs in instruction quality and achieves state-of-the-art performance among open-source methods on reference image conditioned video editing. Our project webpage: https://rebind-mrv2v.github.io/.

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Xinyu Liu, Shihao Li, Weihong Lin, Xinlong Chen, Yang Shi, Yujin Han, Yiyang Cai, Yanghao Wang, Ruibin Yuan, Yuanxing Zhang, Pengfei Wan, Wenhan Luo, Yike Guo. 2026-07-16. ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships. https://arxiv.org/abs/2607.14681

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