7 papers
Dynamic self-ensemble on multi-exit residual vision transformer for small-data image classification
Stephen Ekaputra Limantoro, Yan-Kai Wang, Ching-Chun Huang +4
Vision Transformer (ViT) has garnered increased attention for image classification in recent years. However, ViT is notorious for its data-hungry problem as it achieves high-perfor…
GigaBrain-0.7: Scaling Embodied Foundation Models to Emergent Capabilities with a Three-System Architecture
GigaBrain Team, Angen Ye, Axiang Sun +56
Vision-language-action (VLA) models have become a dominant paradigm for generalist embodied agents, demonstrating strong complex and long-horizon task completion in structured sett…
PointRFT: Explicit Reinforcement Fine-tuning for Point Cloud Few-shot Learning
Yankai Wang, Yiding Sun, Qirui Wang +3
Understanding spatial dynamics and semantics in point cloud is fundamental for comprehensive 3D comprehension. While reinforcement learning algorithms such as Group Relative Policy…
SwarmFoam: An OpenFOAM Multi-Agent System Based on Multiple Types of Large Language Models
Chunwei Yang, Yankai Wang, Jianxiang Tang +6
Numerical simulation is one of the mainstream methods in scientific research, typically performed by professional engineers. With the advancement of multi-agent technology, using c…
GigaWorld-0: World Models as Data Engine to Empower Embodied AI
GigaWorld Team, Angen Ye, Boyuan Wang +22
World models are emerging as a foundational paradigm for scalable, data-efficient embodied AI. In this work, we present GigaWorld-0, a unified world model framework designed explic…
Single-View Scene Point Cloud Human Grasp Generation
Yan-Kang Wang, Chengyi Xing, Yi-Lin Wei +2
In this work, we explore a novel task of generating human grasps based on single-view scene point clouds, which more accurately mirrors the typical real-world situation of observin…
Boundary-induced and scene-aggregated network for monocular depth prediction
Feng Xue, Junfeng Cao, Yu Zhou +3
Monocular depth prediction is an important task in scene understanding. It aims to predict the dense depth of a single RGB image. With the development of deep learning, the perform…