@inproceedings{ma-etal-2026-response,
    title = "Response-G1: Explicit Scene Graph Modeling for Proactive Streaming Video Understanding",
    author = "Ma, Ke  and
      Tang, Jiaqi  and
      Guo, Bin  and
      Han, Xueting  and
      Xu, Ruonan  and
      He, Qingfeng  and
      Wang, Ziheng  and
      Wang, Xu  and
      Chen, Qifeng  and
      Yu, Zhiwen  and
      Liu, Yunhao",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Proceedings of the 64th Annual Meeting of the {A}ssociation for {C}omputational {L}inguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.acl-long.2042/",
    pages = "44139--44153",
    ISBN = "979-8-89176-390-6",
    abstract = "Proactive streaming video understanding requires Video-LLMs to decide when to respond as a video unfolds, a task where existing methods often fall short due to their implicit, query-agnostic modeling of visual evidence. We introduce Response-G1, a novel framework that establishes explicit, structured alignment between the accumulated video evidence and the query{'}s expected response conditions via scene graphs. The framework operates in three fine-tuning-free stages: (1) online query-guided scene graph generation from streaming clips; (2) memory-based retrieval of the most semantically relevant historical scene graphs; and (3) retrieval-augmented trigger prompting for per-frame ``silence/response'' decisions. By grounding both evidence and conditions in a shared graph representation, Response-G1 achieves more interpretable and accurate response timing decisions. Experimental results on established benchmarks demonstrate the superiority of our method in both proactive and reactive tasks, validating the advantage of explicit scene graph modeling and retrieval in streaming video understanding."
}