no code implementations • SemEval (NAACL) 2022 • Jia Fu, Zhen Gan, Zhucong Li, Sirui Li, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao
This paper describes our approach to develop a complex named entity recognition system in SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, Track 9 - Chinese.
no code implementations • SMM4H (COLING) 2022 • Jia Fu, Sirui Li, Hui Ming Yuan, Zhucong Li, Zhen Gan, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu
This paper presents a description of our system in SMM4H-2022, where we participated in task 1a, task 4, and task 6 to task 10.
no code implementations • 7 Mar 2024 • Vindula Jayawardana, Sirui Li, Cathy Wu, Yashar Farid, Kentaro Oguchi
To address this, we introduce Multi-residual Task Learning (MRTL), a generic learning framework based on multi-task learning that, for a set of task scenarios, decomposes the control into nominal components that are effectively solved by conventional control methods and residual terms which are solved using learning.
no code implementations • 6 Feb 2024 • Nishchal Sapkota, Yejia Zhang, Susan M. Motch Perrine, Yuhan Hsi, Sirui Li, Meng Wu, Greg Holmes, Abdul R. Abdulai, Ethylin W. Jabs, Joan T. Richtsmeier, Danny Z Chen
Experiments on the mice cartilage dataset show the superiority of our new model compared to other competitive segmentation models.
1 code implementation • 6 Feb 2024 • Nishchal Sapkota, Yejia Zhang, Sirui Li, Peixian Liang, Zhuo Zhao, Jingjing Zhang, Xiaomin Zha, Yiru Zhou, Yunxia Cao, Danny Z Chen
We propose a new approach for sperm head morphology classification, called SHMC-Net, which uses segmentation masks of sperm heads to guide the morphology classification of sperm images.
no code implementations • 22 Dec 2023 • Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik, Aron Laszka
The increasing reliance of drivers on navigation applications has made transportation networks more susceptible to data-manipulation attacks by malicious actors.
1 code implementation • 17 Dec 2023 • Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao
Besides, existing spatial network representation learning methods can only consider networks embedded in Euclidean space, and can not well exploit the rich geometric information carried by irregular and non-uniform non-Euclidean space.
no code implementations • 11 Oct 2023 • Sirui Li, Roy Dong, Cathy Wu
Through examining the influence of the lane-switch frequency on the system's stability, the analysis offers a principled explanation to the traffic break phenomena, and further discovers opportunities for less-intrusive traffic smoothing by employing less frequent lane-switching.
1 code implementation • 15 Sep 2023 • Michael Stewart, Melinda Hodkiewicz, Sirui Li
In this paper we present the first investigation into the effectiveness of Large Language Models (LLMs) for Failure Mode Classification (FMC).
no code implementations • 10 Jan 2023 • Sirui Li, Roy Dong, Cathy Wu
While previous theoretical studies consider stability analysis for continuous AV control, this article presents the first integrated theoretical analysis that directly relates the guidance provided to the human drivers to the traffic flow stability outcome.
no code implementations • 21 Oct 2022 • Sirui Li, Kok Wai Wong, Dengya Zhu, Chun Che Fung
It is considered that such approaches disconnect the semantic connection of multi-relations between an entity pair, and we propose a convolutional and multi-relational representation learning model, ConvMR.
no code implementations • 16 Oct 2022 • Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu
We show that in comparison to evaluating DRL methods on select MDP instances, evaluating the MDP family often yields a substantially different relative ranking of methods, casting doubt on what methods should be considered state-of-the-art.
1 code implementation • 27 Jul 2022 • Mingjie Wang, Jianxiong Guo, Sirui Li, Dingwen Xiao, Zhiqing Tang
Deep neural networks have significantly advanced person re-identification (ReID) applications in the realm of the industrial internet, yet they remain vulnerable.
no code implementations • 25 Mar 2022 • Sirui Li, Kok Kai Wong, Dengya Zhu, Chun Che Fung
The key idea is to represent questions and entities of a KG as low-dimensional embeddings.
no code implementations • 14 Dec 2021 • Cameron Hickert, Sirui Li, Cathy Wu
A key takeaway is the potential value of cooperation in enabling the deployment of autonomy at scale.
1 code implementation • NeurIPS 2021 • Sirui Li, Zhongxia Yan, Cathy Wu
We frame subproblem selection as regression and train a Transformer on a generated training set of problem instances.
1 code implementation • 6 Jun 2018 • Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan
Work in machine learning and statistics commonly focuses on building models that capture the vast majority of data, possibly ignoring a segment of the population as outliers.