22 citations · 41 across the 14 of their papers we have counts for
7 papers · 1 filter
PhyVLLM: Physics-Guided Video Language Model with Motion-Appearance Disentanglement
Yu-Wei Zhan, Xin Wang, Hong Chen +6
Video Large Language Models (Video LLMs) have shown impressive performance across a wide range of video-language tasks. However, they often fail in scenarios requiring a deeper und…
BiTAgent: A Task-Aware Modular Framework for Bidirectional Coupling between Multimodal Large Language Models and World Models
Yu-Wei Zhan, Xin Wang, Pengzhe Mao +3
Building generalist embodied agents requires a unified system that can interpret multimodal goals, model environment dynamics, and execute reliable actions across diverse real-worl…
Embodied AI: From LLMs to World Models
Tongtong Feng, Xin Wang, Yu-Gang Jiang +1
Embodied Artificial Intelligence (AI) is an intelligent system paradigm for achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications and…
U2UData+: A Scalable Swarm UAVs Autonomous Flight Dataset for Embodied Long-horizon Tasks
Tongtong Feng, Xin Wang, Feilin Han +2
Swarm UAV autonomous flight for Embodied Long-Horizon (ELH) tasks is crucial for advancing the low-altitude economy. However, existing methods focus only on specific basic tasks du…
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards
Zijing Hu, Fengda Zhang, Long Chen +6
Diffusion models have achieved remarkable success in text-to-image generation. However, their practical applications are hindered by the misalignment between generated images and c…
EvolvingAgent: Curriculum Self-evolving Agent with Continual World Model for Long-Horizon Tasks
Tongtong Feng, Xin Wang, Zekai Zhou +5
Completing Long-Horizon (LH) tasks in open-ended worlds is an important yet difficult problem for embodied agents. Existing approaches suffer from two key challenges: (1) they heav…
JAQ: Joint Efficient Architecture Design and Low-Bit Quantization with Hardware-Software Co-Exploration
Mingzi Wang, Yuan Meng, Chen Tang +9
The co-design of neural network architectures, quantization precisions, and hardware accelerators offers a promising approach to achieving an optimal balance between performance an…