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20242026
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cs.CV2026

OmniAssistBench: Assistant-style Interaction Benchmark for Omni-LLMs

Xianyun Sun, Chaoyou Fu, Zhengye Zhang +6

Recent omni-modal large language models (Omni-LLMs) show great potential as real-time video assistants, which continuously perceive environments and guide users to achieve specific…

cs.CV2026

Omni-Prune: Query-Aware Unified Token Pruning for Efficient Omnimodal Large Language Models

Yiming Zhong, Chang Nie, Caifeng Shan

Omnimodal large language models (OmniLLMs) are rapidly extending multimodal reasoning to cover synchronized audio and video. However, the resulting audio-video token sequences are…

cs.CV2026

Light-Omni: Reflex over Reasoning in Agentic Video Understanding with Long-Term Memory

Chang Nie, Jiaju Wei, Junlan Feng +2

Agentic video understanding equips models with long-term memory to autonomously process and respond to continuous, long-horizon multimodal streams. However, advanced video agents o…

cs.CV2026

Omni-Diffusion: Unified Multimodal Understanding and Generation with Masked Discrete Diffusion

Lijiang Li, Zuwei Long, Yunhang Shen +6

While recent multimodal large language models (MLLMs) have made impressive strides, they predominantly employ a conventional autoregressive architecture as their backbone, leaving…

cs.CV2026

OmniVideo-100K: A Dataset for Audio-Visual Reasoning through Structured Scripts and Evidence Chains

Xinyue Cai, Chaoyou Fu, Yi-Fan Zhang +2

Current automated pipelines for audio-visual Question Answering (QA) generally adopt a ``video-caption-QA'' paradigm. However, these methods typically segment videos into short cli…

cs.CV2026

VideoDetective: Clue Hunting via both Extrinsic Query and Intrinsic Relevance for Long Video Understanding

Ruoliu Yang, Chu Wu, Caifeng Shan +2

Long video understanding remains challenging for multimodal large language models (MLLMs) due to limited context windows, which necessitate identifying sparse query-relevant video…