1 code implementation • 10 May 2023 • Long Ma, Kai Lu, Tianbo Che, Hailong Huang, Weiguo Gao, Xuan Li
The MultiCoNER II task aims to detect complex, ambiguous, and fine-grained named entities in low-context situations and noisy scenarios like the presence of spelling mistakes and typos for multiple languages.
no code implementations • 19 Apr 2023 • Fuad Hasan, Hailong Huang
This provides the past trajectory points which then feeds into the trajectory prediction algorithm consisting of an attention-based LSTM encoder-decoder architecture, which allows it to model the complicated interdependence between the vehicles and make an accurate prediction of the future trajectory points of the surrounding vehicles.
no code implementations • 7 Nov 2022 • Harrison Kurunathan, Hailong Huang, Kai Li, Wei Ni, Ekram Hossain
It is also unveiled that the reliability and trust of ML in UAV operations and applications require significant attention before full automation of UAVs and potential cooperation between UAVs and humans come to fruition.
no code implementations • 18 Oct 2021 • Mohsen Eskandari, Hailong Huang, Andrey V. Savkin, Wei Ni
In this work, we propose an RIS-outfitted UAV (RISoUAV) to secure an uninterrupted line-of-sight (LoS) link with a ground moving target (MT).
no code implementations • 24 Sep 2021 • Guang Liu, Hailong Huang, Yuzhao Mao, Weiguo Gao, Xuan Li, Jianping Shen
Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.
1 code implementation • EMNLP 2021 • Guang Liu, Yuzhao Mao, Hailong Huang, Weiguo Gao, Xuan Li
To address these issues, we propose the Adversarial Mixing Policy (AMP), organized in a min-max-rand formulation, to relax the Locally Linear Constraints in Mixup.