5 papers
VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies
Haoxuan Wang, Gengyu Zhang, Yan Yan +2
Action chunking has recently emerged as a standard practice in flow-based Vision-Language-Action (VLA) models. However, the effect and choice of the execution horizon - the number…
You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data
Shanshan Yan, Zexi Li, Chao Wu +4
Data heterogeneity, stemming from local non-IID data and global long-tailed distributions, is a major challenge in federated learning (FL), leading to significant performance gaps…
DPSformer: A long-tail-aware model for improving heavy rainfall prediction
Zenghui Huang, Ting Shu, Zhonglei Wang +4
Accurate and timely forecasting of heavy rainfall remains a critical challenge for modern society. Precipitation exhibits a highly imbalanced distribution: most observations record…
CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model
Shihao Hou, Xinyi Shang, Shreyank N Gowda +4
Effectively handling the co-occurrence of non-IID data and long-tailed distributions remains a critical challenge in federated learning. While fine-tuning vision-language models (V…
Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition
Hanyu Guo, Wanchuan Yu, Suzhou Que +3
In recent years, few-shot action recognition has achieved remarkable performance through spatio-temporal relation modeling. Although a wide range of spatial and temporal alignment…