16 papers
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…
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…
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…
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…
Before Thinking, Learn to Decide: Proactive Routing for Efficient Visual Reasoning
Yinan Zhou, Haokun Lin, Yichen Wu +7
Large multimodal models have achieved strong reasoning on complex visual tasks, but their inference efficiency is often restricted by long chains of thought. A promising solution i…
EvoEmbedding: Evolvable Representations for Long-Context Retrieval and Agentic Memory
Chang Nie, Chaoyou Fu, Junlan Feng +1
Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This paper introduces EvoEmbedding,…