8 papers
The Point, the Vision and the Text: Does Point Cloud Boost Spatial Reasoning of Large Language Models? A Bias-Controlled Study
Weichen Zhang, Ruiying Peng, Xin Zeng +9
3D Large Language Models (LLMs) leveraging spatial information in point clouds for 3D spatial reasoning attract great attention. Despite some promising results, the advantages of p…
Progressive Supernet Training for Efficient Visual Autoregressive Modeling
Xiaoyue Chen, Yuling Shi, Kaiyuan Li +5
Visual Auto-Regressive (VAR) models significantly reduce inference steps through the "next-scale" prediction paradigm. However, progressive multi-scale generation incurs substantia…
Balanced Token Pruning: Accelerating Vision Language Models Beyond Local Optimization
Kaiyuan Li, Xiaoyue Chen, Chen Gao +2
Large Vision-Language Models (LVLMs) have shown impressive performance across multi-modal tasks by encoding images into thousands of tokens. However, the large number of image toke…
AirScape: An Aerial Generative World Model with Motion Controllability
Baining Zhao, Rongze Tang, Mingyuan Jia +9
How to enable agents to predict the outcomes of their own motion intentions in three-dimensional space has been a fundamental problem in embodied intelligence. To explore general s…
EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent
Jiaao Li, Kaiyuan Li, Chen Gao +2
Egomotion videos are first-person recordings where the view changes continuously due to the agent's movement. As they serve as the primary visual input for embodied AI agents, maki…
How to Enable LLM with 3D Capacity? A Survey of Spatial Reasoning in LLM
Jirong Zha, Yuxuan Fan, Xiao Yang +2
3D spatial understanding is essential in real-world applications such as robotics, autonomous vehicles, virtual reality, and medical imaging. Recently, Large Language Models (LLMs)…