6 citations · 6 across the 8 of their papers we have counts for
10 papers
Adaptive Role Assignment and Controlled Feature Reconstruction for Federated Image Semantic Communication
Yuxuan Chen, Jiao Bie, Hang Qi +1
Hybrid federated semantic communication enables user equipment (UEs) to contribute model updates or semantic features under a shared training framework. However, heterogeneous role…
Continual Humanoid Motion Learning
Zhewen He, Hao Huang, Geeta Chandra Raju Bethala +4
Humanoid whole-body controllers can now track a diverse set of dynamic motions, but they are typically trained offline and then frozen, so teaching such a controller a new skill te…
RoboTacDex: A Dexterous Visual-Tactile-Action Dataset for Humanoid Manipulation
Xinyi Wang, Donghan Li, Zi'Ang Chen +5
In the field of robot learning, large-scale and diverse demonstration trajectories provide the fundamental basis for enhancing robotic manipulation ability. We introduce RoboTacDex…
EGM: Efficiently Learning General Motion Tracking Policy for High Dynamic Humanoid Whole-Body Control
Chao Yang, Yingkai Sun, Peng Ye +3
Learning a general motion tracking policy from human motions shows great potential for versatile humanoid whole-body control. Conventional approaches are not only inefficient in da…
S2HPruner: Soft-to-Hard Distillation Bridges the Discretization Gap in Pruning
Weihao Lin, Shengji Tang, Chong Yu +2
Recently, differentiable mask pruning methods optimize the continuous relaxation architecture (soft network) as the proxy of the pruned discrete network (hard network) for superior…
Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression
Hancheng Ye, Chong Yu, Peng Ye +5
Recent Vision Transformer Compression (VTC) works mainly follow a two-stage scheme, where the importance score of each model unit is first evaluated or preset in each submodule, fo…
Enhanced Sparsification via Stimulative Training
Shengji Tang, Weihao Lin, Hancheng Ye +4
Sparsification-based pruning has been an important category in model compression. Existing methods commonly set sparsity-inducing penalty terms to suppress the importance of droppe…
MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer
Jianjian Cao, Peng Ye, Shengze Li +4
Vision-Language Transformers (VLTs) have shown great success recently, but are meanwhile accompanied by heavy computation costs, where a major reason can be attributed to the large…
Efficient Architecture Search via Bi-level Data Pruning
Chongjun Tu, Peng Ye, Weihao Lin +5
Improving the efficiency of Neural Architecture Search (NAS) is a challenging but significant task that has received much attention. Previous works mainly adopted the Differentiabl…
SpVOS: Efficient Video Object Segmentation with Triple Sparse Convolution
Weihao Lin, Tao Chen, Chong Yu
Semi-supervised video object segmentation (Semi-VOS), which requires only annotating the first frame of a video to segment future frames, has received increased attention recently.…