most citedDaily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

VLZip: Unified Visual and Textual Compression for Interleaved Long-Context Modeling

Yuqi Zhang, Cheng Chen, Yuyu Guo +6

Vision Language Models (VLMs) face significant challenges with ultra-long, interleaved image-text sequences due to the quadratic complexity of self-attention. Current solutions eit…

cs.CR2026

Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses

Xiao Li, Xiang Zheng, Yifeng Gao +35

Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, and interaction into agents that operate in open-world, safety-critical environments. As…

cs.CV2026

CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation

Haoyu Zhao, Zihao Zhang, Jiaxi Gu +10

Camera-controllable video generation aims to synthesize videos with flexible and physically plausible camera movements. However, existing methods either provide imprecise camera co…

cs.CV2026

FlashMotion: Few-Step Controllable Video Generation with Trajectory Guidance

Quanhao Li, Zhen Xing, Rui Wang +4

Recent advances in trajectory-controllable video generation have achieved remarkable progress. Previous methods mainly use adapter-based architectures for precise motion control al…

cs.CV2026

WeEdit: A Dataset, Benchmark and Glyph-Guided Framework for Text-centric Image Editing

Hui Zhang, Juntao Liu, Zongkai Liu +4

Instruction-based image editing aims to modify specific content within existing images according to user-provided instructions while preserving non-target regions. Beyond tradition…

cs.AI2026

Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities

Ziwei Zhou, Rui Wang, Zuxuan Wu +1

Recent Multimodal Large Language Models (MLLMs) achieve promising performance on visual and audio benchmarks independently. However, the ability of these models to process cross-mo…