70 citations · 79 across the 6 of their papers we have counts for
6 papers
DAP: Domain-aware Prompt Learning for Vision-and-Language Navigation
Ting Liu, Yue Hu, Wansen Wu +3
Following language instructions to navigate in unseen environments is a challenging task for autonomous embodied agents. With strong representation capabilities, pretrained vision-…
Prompt-based Context- and Domain-aware Pretraining for Vision and Language Navigation
Ting Liu, Yue Hu, Wansen Wu +3
Pretrained visual-language models have extensive world knowledge and are widely used in visual and language navigation (VLN). However, they are not sensitive to indoor scenarios fo…
Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps
Yue Hu, Shaoheng Fang, Zixing Lei +2
Multi-agent collaborative perception could significantly upgrade the perception performance by enabling agents to share complementary information with each other through communicat…
FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity
Guanghao Li, Yue Hu, Miao Zhang +4
Federated Learning (FL) enables training a global model without sharing the decentralized raw data stored on multiple devices to protect data privacy. Due to the diverse capacity o…
Who Are the `Silent Spreaders'?: Contact Tracing in Spatio-Temporal Memory Models
Yue Hu, Budhitama Subagdja, Ah-Hwee Tan +2
The COVID-19 epidemic has swept the world for over a year. However, a large number of infectious asymptomatic COVID-19 cases (\textit{ACC}s) are still making the breaking up of the…
Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder
Junjie Zeng, Long Qin, Yue Hu +2
In this paper, we present a hierarchical path planning framework called SG-RL (subgoal graphs-reinforcement learning), to plan rational paths for agents maneuvering in continuous a…