2 citations · 4 across the 6 of their papers we have counts for
7 papers
Navi-Agent: Unlocalized Monocular Navigation Agent
Wenyuan Xie, Mengyang Hong, Yongzhong Wang +9
Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to execute long-horizon instructions in unknown environments. Existing zero-shot VLN-CE sy…
Discretized Gaussian Representation for Tomographic Reconstruction
Shaokai Wu, Yuxiang Lu, Yapan Guo +9
Computed Tomography (CT) enables detailed cross-sectional imaging but continues to face challenges in balancing reconstruction quality and computational efficiency. While deep lear…
Task Indicating Transformer for Task-conditional Dense Predictions
Yuxiang Lu, Shalayiding Sirejiding, Bayram Bayramli +3
The task-conditional model is a distinctive stream for efficient multi-task learning. Existing works encounter a critical limitation in learning task-agnostic and task-specific rep…
YOLO-MED : Multi-Task Interaction Network for Biomedical Images
Suizhi Huang, Shalayiding Sirejiding, Yuxiang Lu +4
Object detection and semantic segmentation are pivotal components in biomedical image analysis. Current single-task networks exhibit promising outcomes in both detection and segmen…
Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study
Yuwen Yang, Yuxiang Lu, Suizhi Huang +3
The innovative Federated Multi-Task Learning (FMTL) approach consolidates the benefits of Federated Learning (FL) and Multi-Task Learning (MTL), enabling collaborative model traini…
FedHCA: Towards Hetero-Client Federated Multi-Task Learning
Yuxiang Lu, Suizhi Huang, Yuwen Yang +3
Federated Learning (FL) enables joint training across distributed clients using their local data privately. Federated Multi-Task Learning (FMTL) builds on FL to handle multiple tas…
Prompt Guided Transformer for Multi-Task Dense Prediction
Yuxiang Lu, Shalayiding Sirejiding, Yue Ding +2
Task-conditional architecture offers advantage in parameter efficiency but falls short in performance compared to state-of-the-art multi-decoder methods. How to trade off performan…