1 citations · 1 across the 2 of their papers we have counts for
6 papers
Confidence-driven Gradient Modulation for Multimodal Human Activity Recognition: A Dynamic Contrastive Dual-Path Learning Approach
Panpan Ji, Junni Song, Yifan Lu +3
Sensor-based Human Activity Recognition (HAR) is a core technology that enables intelligent systems to perceive and interact with their environment. However, multimodal HAR systems…
CombatVLA: An Efficient Vision-Language-Action Model for Combat Tasks in 3D Action Role-Playing Games
Peng Chen, Pi Bu, Yingyao Wang +9
Recent advances in Vision-Language-Action models (VLAs) have expanded the capabilities of embodied intelligence. However, significant challenges remain in real-time decision-making…
Global Compression Commander: Plug-and-Play Inference Acceleration for High-Resolution Large Vision-Language Models
Xuyang Liu, Ziming Wang, Junjie Chen +6
Large vision-language models (LVLMs) excel at visual understanding, but face efficiency challenges due to quadratic complexity in processing long multi-modal contexts. While token…
LLaVA-UHD v2: an MLLM Integrating High-Resolution Semantic Pyramid via Hierarchical Window Transformer
Yipeng Zhang, Yifan Liu, Zonghao Guo +10
Vision transformers (ViTs) are widely employed in multimodal large language models (MLLMs) for visual encoding. However, they exhibit inferior performance on tasks regarding fine-g…
FILA: Fine-Grained Vision Language Models
Shiding Zhu, Wenhui Dong, Jun Song +3
Recently, there has been growing interest in the capability of multimodal large language models (MLLMs) to process high-resolution images. A common approach currently involves dyna…
Can VLMs Play Action Role-Playing Games? Take Black Myth Wukong as a Study Case
Peng Chen, Pi Bu, Jun Song +2
Recently, large language model (LLM)-based agents have made significant advances across various fields. One of the most popular research areas involves applying these agents to vid…