7 citations · 15 across the 8 of their papers we have counts for
8 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…
DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learning
Qinglun Li, Li Shen, Guanghao Li +2
To address the communication burden issues associated with federated learning (FL), decentralized federated learning (DFL) discards the central server and establishes a decentraliz…
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…
How to Evaluate Your Dialogue Models: A Review of Approaches
Xinmeng Li, Wansen Wu, Long Qin +1
Evaluating the quality of a dialogue system is an understudied problem. The recent evolution of evaluation method motivated this survey, in which an explicit and comprehensive anal…
Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction
Xinmeng Li, Mamoun Alazab, Qian Li +2
Knowledge graph question answering is an important technology in intelligent human-robot interaction, which aims at automatically giving answer to human natural language question w…
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…