5 papers
LLaVA-Scissor: Token Compression with Semantic Connected Components for Video LLMs
Boyuan Sun, Jiaxing Zhao, Xihan Wei +1
In this paper, we present LLaVA-Scissor, a training-free token compression strategy designed for video multimodal large language models. Previous methods mostly attempt to compress…
HumanOmniV2: From Understanding to Omni-Modal Reasoning with Context
Qize Yang, Shimin Yao, Weixuan Chen +7
With the rapid evolution of multimodal large language models, the capacity to deeply understand and interpret human intentions has emerged as a critical capability, which demands d…
R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning
Jiaxing Zhao, Xihan Wei, Liefeng Bo
In this work, we present the first application of Reinforcement Learning with Verifiable Reward (RLVR) to an Omni-multimodal large language model in the context of emotion recognit…
HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding
Jiaxing Zhao, Qize Yang, Yixing Peng +8
In human-centric scenes, the ability to simultaneously understand visual and auditory information is crucial. While recent omni models can process multiple modalities, they general…
Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual Awareness
Jiaxing Zhao, Boyuan Sun, Xiang Chen +1
Facial expression captioning has found widespread application across various domains. Recently, the emergence of video Multimodal Large Language Models (MLLMs) has shown promise in…