25 citations · 46 across the 50 of their papers we have counts for
9 papers · 1 filter
Score and Distribution Matching Policy: Advanced Accelerated Visuomotor Policies via Matched Distillation
Bofang Jia, Pengxiang Ding, Can Cui +5
Visual-motor policy learning has advanced with architectures like diffusion-based policies, known for modeling complex robotic trajectories. However, their prolonged inference time…
QUART-Online: Latency-Free Large Multimodal Language Model for Quadruped Robot Learning
Xinyang Tong, Pengxiang Ding, Yiguo Fan +9
This paper addresses the inherent inference latency challenges associated with deploying multimodal large language models (MLLM) in quadruped vision-language-action (QUAR-VLA) task…
CARP: Visuomotor Policy Learning via Coarse-to-Fine Autoregressive Prediction
Zhefei Gong, Pengxiang Ding, Shangke Lyu +5
In robotic visuomotor policy learning, diffusion-based models have achieved significant success in improving the accuracy of action trajectory generation compared to traditional au…
Filter, Correlate, Compress: Training-Free Token Reduction for MLLM Acceleration
Yuhang Han, Xuyang Liu, Zihan Zhang +6
The quadratic complexity of Multimodal Large Language Models (MLLMs) with respect to context length poses significant computational and memory challenges, hindering their real-worl…
ProFD: Prompt-Guided Feature Disentangling for Occluded Person Re-Identification
Can Cui, Siteng Huang, Wenxuan Song +3
To address the occlusion issues in person Re-Identification (ReID) tasks, many methods have been proposed to extract part features by introducing external spatial information. Howe…
PiTe: Pixel-Temporal Alignment for Large Video-Language Model
Yang Liu, Pengxiang Ding, Siteng Huang +3
Fueled by the Large Language Models (LLMs) wave, Large Visual-Language Models (LVLMs) have emerged as a pivotal advancement, bridging the gap between image and text. However, video…
GeRM: A Generalist Robotic Model with Mixture-of-experts for Quadruped Robot
Wenxuan Song, Han Zhao, Pengxiang Ding +4
Multi-task robot learning holds significant importance in tackling diverse and complex scenarios. However, current approaches are hindered by performance issues and difficulties in…
Towards more realistic human motion prediction with attention to motion coordination
Pengxiang Ding, Jianqin Yin
Joint relation modeling is a curial component in human motion prediction. Most existing methods rely on skeletal-based graphs to build the joint relations, where local interactive…
Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference
Han Zhao, Min Zhang, Wei Zhao +3
In recent years, the application of multimodal large language models (MLLM) in various fields has achieved remarkable success. However, as the foundation model for many downstream…