Search Results for author: Zhuang Li

Found 21 papers, 7 papers with code

Active Learning for Multilingual Semantic Parser

no code implementations30 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.

Active Learning Semantic Parsing +1

Let's Negotiate! A Survey of Negotiation Dialogue Systems

no code implementations18 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.

Strong Instance Segmentation Pipeline for MMSports Challenge

1 code implementation28 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.

Data Augmentation Instance Segmentation +1

Real-time End-to-End Video Text Spotter with Contrastive Representation Learning

no code implementations18 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.

Contrastive Learning Representation Learning +1

The Third Place Solution for CVPR2022 AVA Accessibility Vision and Autonomy Challenge

no code implementations28 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.

Data Augmentation

The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation

no code implementations24 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.

object-detection Object Detection +4

A Zipf's Law-Driven Method for Extracting Entities from Documents

no code implementations25 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.

Text Generation

Paraphrasing Techniques for Maritime QA system

no code implementations21 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.

Variational Autoencoder with Disentanglement Priors for Low-Resource Task-Specific Natural Language Generation

1 code implementation27 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.

Data Augmentation Disentanglement +3

Contrastive Learning of Semantic and Visual Representations for Text Tracking

no code implementations30 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.

Contrastive Learning

Pretrained Language Model in Continual Learning: A Comparative Study

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.

Continual Learning Language Modelling

Total Recall: a Customized Continual Learning Method for Neural Semantic Parsers

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.

Continual Learning Semantic Parsing

AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation

1 code implementation11 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.

Image Augmentation Image Classification +3

Representation Learning for Weakly Supervised Relation Extraction

no code implementations10 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.

Relation Extraction Representation Learning +1

On Robustness of Neural Semantic Parsers

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.

Data Augmentation Semantic Parsing

Context Dependent Semantic Parsing: A Survey

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.

Semantic Parsing

Asymmetric Correntropy for Robust Adaptive Filtering

no code implementations21 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.

Cannot find the paper you are looking for? You can Submit a new open access paper.