21 citations · 22 across the 10 of their papers we have counts for
11 papers
Orca: The World is in Your Mind
Yihao Wang, Yuheng Ji, Mingyu Cao +54
We introduce Orca, an initial instantiation of a general world foundation model. Orca learns a unified world latent space from multimodal world signals and exposes it through multi…
RoboBrain 2.5: Depth in Sight, Time in Mind
Huajie Tan, Enshen Zhou, Zhiyu Li +32
We introduce RoboBrain 2.5, a next-generation embodied AI foundation model that advances general perception, spatial reasoning, and temporal modeling through extensive training on…
RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation
Shihan Wu, Xuecheng Liu, Shaoxuan Xie +81
Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due to the significant hardware hete…
Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain
Yulin Luo, Chun-Kai Fan, Menghang Dong +19
Building robots that can perceive, reason, and act in dynamic, unstructured environments remains a central challenge. Recent embodied systems often follow a dual-system paradigm, w…
Orochi: Versatile Biomedical Image Processor
Gaole Dai, Chenghao Zhou, Yu Zhou +6
Deep learning has emerged as a pivotal tool for accelerating research in the life sciences, with the low-level processing of biomedical images (e.g., registration, fusion, restorat…
SpikePingpong: Spike Vision-based Fast-Slow Pingpong Robot System
Hao Wang, Chengkai Hou, Xianglong Li +7
Learning to control high-speed objects in dynamic environments represents a fundamental challenge in robotics. Table tennis serves as an ideal testbed for advancing robotic capabil…
RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics
Enshen Zhou, Jingkun An, Cheng Chi +8
Spatial referring is a fundamental capability of embodied robots to interact with the 3D physical world. However, even with the powerful pretrained vision language models (VLMs), r…
SpikeGen: Decoupled "Rods and Cones" Visual Representation Processing with Latent Generative Framework
Gaole Dai, Menghang Dong, Rongyu Zhang +3
The process through which humans perceive and learn visual representations in dynamic environments is highly complex. From a structural perspective, the human eye decouples the fun…
SAN: Hypothesizing Long-Term Synaptic Development and Neural Engram Mechanism in Scalable Model's Parameter-Efficient Fine-Tuning
Gaole Dai, Chun-Kai Fan, Yiming Tang +7
Advances in Parameter-Efficient Fine-Tuning (PEFT) bridged the performance gap with Full Fine-Tuning (FFT) through sophisticated analysis of pre-trained parameter spaces. Starting…
Multimodal Large Language Models for Bioimage Analysis
Shanghang Zhang, Gaole Dai, Tiejun Huang +1
Rapid advancements in imaging techniques and analytical methods over the past decade have revolutionized our ability to comprehensively probe the biological world at multiple scale…
Implicit Neural Image Field for Biological Microscopy Image Compression
Gaole Dai, Cheng-Ching Tseng, Qingpo Wuwu +9
The rapid pace of innovation in biological microscopy imaging has led to large images, putting pressure on data storage and impeding efficient sharing, management, and visualizatio…