arXiv:2511. 23304v2 Announce Type: replace Abstract: In this paper, we propose a novel Multi-Modal Scene Graph with Kolmogorov-Arnold Expert Network for Audio-Visual Question Answering (SHRIKE).
By Zijian Fu, Changsheng Lv, Xianlin Zhang, Mengshi Qi, Huadong Ma
arXiv:2610.32268v1 Announce Type: new
Abstract: Existing temporal video grounding (TVG) benchmarks primarily focus on localizing target video segments according to descriptive text queries of the vis...
By Yue Feng, Boshen Xu, Zihao Yue, Xiaokun Liu, Miao Yang, Xin Tao, Pengfei Wan, Qin Jin
arXiv:2607. 03825v1 Announce Type: cross Abstract: Audio-Visual Question Answering (AVQA) extends classical VQA by requiring joint reasoning over video and synchronized audio.
By SungHun Kim, SeungJun Baek
arXiv:2608. 09435v1 Announce Type: new Abstract: Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time.
By Zhi Zeng, Cheng Zhang, Zesheng Yang, Rendong Pi, Jiaying Wu, Di Zhang, Zihan Ma, Guodong Li, Zhou Yang, Yu Xiang, Yifei Zheng, Minnan Luo
Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time. Yet existing audio-language models often represent clips as global acoustic events, while vision-language models lack the spatial audio cues needed to localize and track individual sources.
The paper introduces Omni-Interactive Universal Embedder (OmniUE), a unified embedding framework that learns a single representation space for text, video, and audio using learnable tokens and intermediate-layer representations. OmniUE supports omni-interactive querying, allowing users to input text, visual regions, or audio spans, which are processed by segmenters and an omni-LLM to generate user-conditioned embeddings. The authors evaluate OmniUE on the new OmniCHOIR benchmark and other multimodal tasks, reporting significant performance gains over state‑of‑the‑art baselines across textual, audio, and visual interactive settings.
By Wei-Yao Wang, Kazuya Tateishi, Shuyang Cui, Christian Simon, Takashi Shibuya, Shusuke Takahashi, Yuki Mitsufuji