no code implementations • 30 Jan 2023 • Terry Yue Zhuo, Zhuang Li, Yujin Huang, Fatemeh Shiri, Weiqing Wang, Gholamreza Haffari, Yuan-Fang Li
Semantic parsing is a technique aimed at constructing a structured representation of the meaning of a natural-language question.
no code implementations • 30 Jan 2023 • Zhuang Li, Gholamreza Haffari
Current multilingual semantic parsing (MSP) datasets are almost all collected by translating the utterances in the existing datasets from the resource-rich language to the target language.
no code implementations • 18 Dec 2022 • Haolan Zhan, YuFei Wang, Tao Feng, Yuncheng Hua, Suraj Sharma, Zhuang Li, Lizhen Qu, Gholamreza Haffari
Negotiation is one of the crucial abilities in human communication, and there has been a resurgent research interest in negotiation dialogue systems recently, which goal is to empower intelligent agents with such ability that can efficiently help humans resolve conflicts or reach beneficial agreements.
1 code implementation • 28 Sep 2022 • Bo Yan, Fengliang Qi, Zhuang Li, Yadong Li, Hongbin Wang
The goal of ACM MMSports2022 DeepSportRadar Instance Segmentation Challenge is to tackle the segmentation of individual humans including players, coaches and referees on a basketball court.
no code implementations • 18 Jul 2022 • Wejia Wu, Zhuang Li, Jiahong Li, Chunhua Shen, Hong Zhou, Size Li, Zhongyuan Wang, Ping Luo
Our contributions are three-fold: 1) CoText simultaneously address the three tasks (e. g., text detection, tracking, recognition) in a real-time end-to-end trainable framework.
no code implementations • 28 Jun 2022 • Bo Yan, Leilei Cao, Zhuang Li, Hongbin Wang
Finally, our approach achieves 63. 008\%AP@0. 50:0. 95 on the test set of CVPR2022 AVA Challenge.
no code implementations • 24 Jun 2022 • Leilei Cao, Zhuang Li, Bo Yan, Feng Zhang, Fengliang Qi, Yuchen Hu, Hongbin Wang
The referring video object segmentation task (RVOS) aims to segment object instances in a given video referred by a language expression in all video frames.
no code implementations • 25 May 2022 • Zhenhua Wang, Ming Ren, Dong Gao, Zhuang Li
Entity extraction is critical to the intelligent development of various domains and the construction of knowledge agents.
no code implementations • 21 Mar 2022 • Fatemeh Shiri, Terry Yue Zhuo, Zhuang Li, Van Nguyen, Shirui Pan, Weiqing Wang, Reza Haffari, Yuan-Fang Li
In this paper, we investigate how to exploit paraphrasing methods for the automated generation of large-scale training datasets (in the form of paraphrased utterances and their corresponding logical forms in SQL format) and present our experimental results using real-world data in the maritime domain.
1 code implementation • 27 Feb 2022 • Zhuang Li, Lizhen Qu, Qiongkai Xu, Tongtong Wu, Tianyang Zhan, Gholamreza Haffari
In this paper, we propose a variational autoencoder with disentanglement priors, VAE-DPRIOR, for task-specific natural language generation with none or a handful of task-specific labeled examples.
no code implementations • 30 Dec 2021 • Zhuang Li, Weijia Wu, Mike Zheng Shou, Jiahong Li, Size Li, Zhongyuan Wang, Hong Zhou
Semantic representation is of great benefit to the video text tracking(VTT) task that requires simultaneously classifying, detecting, and tracking texts in the video.
3 code implementations • 9 Dec 2021 • Weijia Wu, Yuanqiang Cai, Debing Zhang, Sibo Wang, Zhuang Li, Jiahong Li, Yejun Tang, Hong Zhou
Most existing video text spotting benchmarks focus on evaluating a single language and scenario with limited data.
no code implementations • ICLR 2022 • Tongtong Wu, Massimo Caccia, Zhuang Li, Yuan-Fang Li, Guilin Qi, Gholamreza Haffari
In this paper, we thoroughly compare the continual learning performance over the combination of 5 PLMs and 4 veins of CL methods on 3 benchmarks in 2 typical incremental settings.
1 code implementation • EMNLP 2021 • Zhuang Li, Lizhen Qu, Gholamreza Haffari
We conduct extensive experiments to study the research problems involved in continual semantic parsing and demonstrate that a neural semantic parser trained with TotalRecall achieves superior performance than the one trained directly with the SOTA continual learning algorithms and achieve a 3-6 times speedup compared to re-training from scratch.
1 code implementation • 11 Jun 2021 • Mingxiang Chen, Zhanguo Chang, Haonan Lu, Bitao Yang, Zhuang Li, Liufang Guo, Zhecheng Wang
In our evaluations, the method outperforms all the state-of-the-art image retrieval algorithms on some out-of-domain image datasets.
no code implementations • 10 Apr 2021 • Zhuang Li
The experiments have demonstrated that this type of feature, combine with the traditional hand-crafted features, could improve the performance of the logistic classification model for relation extraction, especially on the classification of relations with only minor training instances.
no code implementations • EACL 2021 • Shuo Huang, Zhuang Li, Lizhen Qu, Lei Pan
In this paper, we provide the empirical study on the robustness of semantic parsers in the presence of adversarial attacks.
1 code implementation • EACL 2021 • Zhuang Li, Lizhen Qu, Shuo Huang, Gholamreza Haffari
In this work, we investigate the problems of semantic parsing in a few-shot learning setting.
1 code implementation • COLING 2020 • Zhuang Li, Lizhen Qu, Gholamreza Haffari
Semantic parsing is the task of translating natural language utterances into machine-readable meaning representations.
no code implementations • 21 Nov 2019 • Badong Chen, Yuqing Xie, Zhuang Li, Yingsong Li, Pengju Ren
Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables.