1 code implementation • 15 Mar 2024 • Xinrun Xu, Yuxin Wang, Chaoyi Xu, Ziluo Ding, Jiechuan Jiang, Zhiming Ding, Börje F. Karlsson
The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry.
2 code implementations • 5 Mar 2024 • Weihao Tan, Ziluo Ding, Wentao Zhang, Boyu Li, Bohan Zhou, Junpeng Yue, Haochong Xia, Jiechuan Jiang, Longtao Zheng, Xinrun Xu, Yifei Bi, Pengjie Gu, Xinrun Wang, Börje F. Karlsson, Bo An, Zongqing Lu
Despite the success in specific tasks and scenarios, existing foundation agents, empowered by large models (LMs) and advanced tools, still cannot generalize to different scenarios, mainly due to dramatic differences in the observations and actions across scenarios.
no code implementations • 3 Feb 2024 • Haobin Jiang, Ziluo Ding, Zongqing Lu
The other is how agents can explore in a coordinated way.
no code implementations • 19 Jan 2024 • Liwen Hu, Ziluo Ding, Mianzhi Liu, Lei Ma, Tiejun Huang
In this paper, we propose a bidirectional recurrent-based reconstruction framework, including a Light-Robust Representation (LR-Rep) and a fusion module, to better handle such extreme conditions.
1 code implementation • 19 Mar 2023 • Ziluo Ding, Hao Luo, Ke Li, Junpeng Yue, Tiejun Huang, Zongqing Lu
One of the essential missions in the AI research community is to build an autonomous embodied agent that can attain high-level performance across a wide spectrum of tasks.
no code implementations • 25 Oct 2022 • Ziluo Ding, Wanpeng Zhang, Junpeng Yue, Xiangjun Wang, Tiejun Huang, Zongqing Lu
We investigate the use of natural language to drive the generalization of policies in multi-agent settings.
Multi-agent Reinforcement Learning reinforcement-learning +1
no code implementations • 26 Sep 2022 • Ziluo Ding, Kefan Su, Weixin Hong, Liwen Zhu, Tiejun Huang, Zongqing Lu
Communication helps agents to obtain information about others so that better coordinated behavior can be learned.
1 code implementation • CVPR 2022 • Liwen Hu, Rui Zhao, Ziluo Ding, Lei Ma, Boxin Shi, Ruiqin Xiong, Tiejun Huang
Further, for training SCFlow, we synthesize two sets of optical flow data for the spiking camera, SPIkingly Flying Things and Photo-realistic High-speed Motion, denoted as SPIFT and PHM respectively, corresponding to random high-speed and well-designed scenes.
no code implementations • 29 Sep 2021 • Ziluo Ding, Weixin Hong, Liwen Zhu, Tiejun Huang, Zongqing Lu
Agents determine the priority of decision-making by comparing the value of intention.
1 code implementation • 10 Sep 2021 • Ziluo Ding, Rui Zhao, Jiyuan Zhang, Tianxiao Gao, Ruiqin Xiong, Zhaofei Yu, Tiejun Huang
Recently, many deep learning methods have shown great success in providing promising solutions to many event-based problems, such as optical flow estimation.
no code implementations • 1 Jan 2021 • Ziluo Ding, Tiejun Huang, Zongqing Lu
The emergence of language is a mystery.
1 code implementation • NeurIPS 2020 • Ziluo Ding, Tiejun Huang, Zongqing Lu
Empirically, we show that I2C can not only reduce communication overhead but also improve the performance in a variety of multi-agent cooperative scenarios, comparing to existing methods.