Search Results for author: Jun Zhao

Found 198 papers, 38 papers with code

Scene Restoring for Narrative Machine Reading Comprehension

no code implementations EMNLP 2020 Zhixing Tian, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yantao Jia, Zhicheng Sheng

Inspired by this behavior of humans, we propose a method to let the machine imagine a scene during reading narrative for better comprehension.

Cloze Test Machine Reading Comprehension +1

Generating Temporally-ordered Event Sequences via Event Optimal Transport

no code implementations COLING 2022 Bo Zhou, Yubo Chen, Kang Liu, Jun Zhao, Jiexin Xu, XiaoJian Jiang, Qiuxia Li

The other issue is that the model adopts a word-level objective to model events in texts, failing to evaluate the predicted results of the model from the perspective of event sequence.

Augmentation, Retrieval, Generation: Event Sequence Prediction with a Three-Stage Sequence-to-Sequence Approach

no code implementations COLING 2022 Bo Zhou, Chenhao Wang, Yubo Chen, Kang Liu, Jun Zhao, Jiexin Xu, XiaoJian Jiang, Qiuxia Li

Currently existing approach models this task as a statistical induction problem, to predict a sequence of events by exploring the similarity between the given goal and the known sequences of events.


CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers

1 code implementation COLING 2022 Yiming Ju, Weikang Wang, Yuanzhe Zhang, Suncong Zheng, Kang Liu, Jun Zhao

To bridge the gap, we propose a new task: conditional question answering with hierarchical multi-span answers, where both the hierarchical relations and the conditions need to be extracted.

Question Answering

Leveraging Explicit Lexico-logical Alignments in Text-to-SQL Parsing

no code implementations ACL 2022 Runxin Sun, Shizhu He, Chong Zhu, Yaohan He, Jinlong Li, Jun Zhao, Kang Liu

Text-to-SQL aims to parse natural language questions into SQL queries, which is valuable in providing an easy interface to access large databases.

SQL Parsing Text-To-SQL

CASIA at SemEval-2022 Task 11: Chinese Named Entity Recognition for Complex and Ambiguous Entities

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.

Chinese Named Entity Recognition Data Augmentation +3

Uncertain Local-to-Global Networks for Document-Level Event Factuality Identification

1 code implementation EMNLP 2021 Pengfei Cao, Yubo Chen, Yuqing Yang, Kang Liu, Jun Zhao

Moreover, we propose an Uncertain Information Aggregation module to leverage the global structure for integrating the local information.

Biomedical Concept Normalization by Leveraging Hypernyms

1 code implementation EMNLP 2021 Cheng Yan, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yafei Shi, Shengping Liu

Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module.

Set Generation Networks for End-to-End Knowledge Base Population

no code implementations EMNLP 2021 Dianbo Sui, Chenhao Wang, Yubo Chen, Kang Liu, Jun Zhao, Wei Bi

In this paper, we formulate end-to-end KBP as a direct set generation problem, avoiding considering the order of multiple facts.

Knowledge Base Population Machine Translation

CroAno : A Crowd Annotation Platform for Improving Label Consistency of Chinese NER Dataset

no code implementations EMNLP (ACL) 2021 Baoli Zhang, Zhucong Li, Zhen Gan, Yubo Chen, Jing Wan, Kang Liu, Jun Zhao, Shengping Liu, Yafei Shi

2) Inconsistency Detector: CroAno employs a detector to locate corpus-level label inconsistency and provides users an interface to correct inconsistent entities in batches.

Chinese Named Entity Recognition Management +3

Incremental Event Detection via Knowledge Consolidation Networks

no code implementations EMNLP 2020 Pengfei Cao, Yubo Chen, Jun Zhao, Taifeng Wang

However, existing incremental learning methods cannot handle semantic ambiguity and training data imbalance problems between old and new classes in the task of incremental event detection.

Event Detection Incremental Learning

FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction

no code implementations EMNLP 2020 Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, Weijian Sun

In this paper, we propose a privacy-preserving medical relation extraction model based on federated learning, which enables training a central model with no single piece of private local data being shared or exchanged.

Federated Learning Knowledge Distillation +3

Knowledge Transfer with Visual Prompt in multi-modal Dialogue Understanding and Generation

no code implementations TU (COLING) 2022 Minjun Zhu, Yixuan Weng, Bin Li, Shizhu He, Kang Liu, Jun Zhao

In this work, we propose a knowledge transfer method with visual prompt (VPTG) fusing multi-modal data, which is a flexible module that can utilize the text-only seq2seq model to handle visual dialogue tasks.

Dialogue Understanding Knowledge Distillation +2

Read Extensively, Focus Smartly: A Cross-document Semantic Enhancement Method for Visual Documents NER

no code implementations COLING 2022 Jun Zhao, Xin Zhao, WenYu Zhan, Tao Gui, Qi Zhang, Liang Qiao, Zhanzhan Cheng, ShiLiang Pu

To deal with this problem, this work proposes a cross-document semantic enhancement method, which consists of two modules: 1) To prevent distractions from irrelevant regions in the current document, we design a learnable attention mask mechanism, which is used to adaptively filter redundant information in the current document.


Towards Graph-hop Retrieval and Reasoning in Complex Question Answering over Textual Database

no code implementations23 May 2023 Minjun Zhu, Yixuan Weng, Shizhu He, Kang Liu, Jun Zhao

In Textual question answering (TQA) systems, complex questions often require retrieving multiple textual fact chains with multiple reasoning steps.

Question Answering Retrieval

S$^3$HQA: A Three-Stage Approach for Multi-hop Text-Table Hybrid Question Answering

1 code implementation19 May 2023 Fangyu Lei, Xiang Li, Yifan Wei, Shizhu He, Yiming Huang, Jun Zhao, Kang Liu

In this paper, we propose a three-stage TextTableQA framework S3HQA, which comprises of retriever, selector, and reasoner.

Question Answering Reading Comprehension

Large Language Models Need Holistically Thought in Medical Conversational QA

1 code implementation9 May 2023 Yixuan Weng, Bin Li, Fei Xia, Minjun Zhu, Bin Sun, Shizhu He, Kang Liu, Jun Zhao

The medical conversational question answering (CQA) system aims at providing a series of professional medical services to improve the efficiency of medical care.

Conversational Question Answering

Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning Question

no code implementations5 May 2023 Yifan Wei, Fangyu Lei, Yuanzhe Zhang, Jun Zhao, Kang Liu

Hybrid question answering (HybridQA) over the financial report contains both textual and tabular data, and requires the model to select the appropriate evidence for the numerical reasoning task.

Graph Representation Learning Machine Reading Comprehension +1

Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks

1 code implementation4 Apr 2023 Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao

Language models (LMs) proficiency in handling deterministic symbolic reasoning and rule-based tasks remains limited due to their dependency implicit learning on textual data.

Arithmetic Reasoning Language Modelling

Towards Adversarially Robust Continual Learning

no code implementations31 Mar 2023 Tao Bai, Chen Chen, Lingjuan Lyu, Jun Zhao, Bihan Wen

Recent studies show that models trained by continual learning can achieve the comparable performances as the standard supervised learning and the learning flexibility of continual learning models enables their wide applications in the real world.

Adversarial Robustness Continual Learning

Detection of Uncertainty in Exceedance of Threshold (DUET): An Adversarial Patch Localizer

no code implementations18 Mar 2023 Terence Jie Chua, Wenhan Yu, Jun Zhao

We then conduct further analyses on our choice of model priors and the adoption of Bayesian Neural Networks in different layers within our model architecture.

Self-Driving Cars

Mobile Edge Adversarial Detection for Digital Twinning to the Metaverse with Deep Reinforcement Learning

no code implementations18 Mar 2023 Terence Jie Chua, Wenhan Yu, Jun Zhao

Nevertheless, as real-time, accurate detection of adversarial patches is compute-intensive, these physical world scenes have to be offloaded to the Metaverse Map Base Stations (MMBS) for computation.

Virtual Reality in Metaverse over Wireless Networks with User-centered Deep Reinforcement Learning

no code implementations8 Mar 2023 Wenhan Yu, Terence Jie Chua, Jun Zhao

Virtual reality (VR) technologies are the backbone for the virtual universe within the Metaverse as they enable a hyper-realistic and immersive experience, and especially so in the context of socialization.

User-centric Heterogeneous-action Deep Reinforcement Learning for Virtual Reality in the Metaverse over Wireless Networks

no code implementations3 Feb 2023 Wenhan Yu, Terence Jie Chua, Jun Zhao

In this paper, for a system consisting of a Metaverse server and multiple VR users, we consider two cases of (i) the server generating frames and transmitting them to users, and (ii) users generating frames locally and thus consuming device energy.

Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules

no code implementations7 Jan 2023 Yinyu Lan, Shizhu He, Kang Liu, Jun Zhao

The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs.

Knowledge Graph Embeddings Question Answering

UAV aided Metaverse over Wireless Communications: A Reinforcement Learning Approach

no code implementations4 Jan 2023 Peiyuan Si, Wenhan Yu, Jun Zhao, Kwok-Yan Lam, Qing Yang

A huge amount of data in physical world needs to be synchronized to the virtual world to provide immersive experience for users, and there will be higher requirements on coverage to include more users into Metaverse.

reinforcement-learning Reinforcement Learning (RL)

Large Language Models are Better Reasoners with Self-Verification

1 code implementation19 Dec 2022 Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao

Recently, with the chain of thought (CoT) prompting, large language models (LLMs), e. g., GPT-3, have shown strong reasoning ability in several natural language processing tasks such as arithmetic, commonsense, and logical reasoning.

Arithmetic Reasoning Common Sense Reasoning +3

Unified, User and Task (UUT) Centered Artificial Intelligence for Metaverse Edge Computing

no code implementations19 Dec 2022 Terence Jie Chua, Wenhan Yu, Jun Zhao

The Metaverse can be considered the extension of the present-day web, which integrates the physical and virtual worlds, delivering hyper-realistic user experiences.


Mobile Augmented Reality with Federated Learning in the Metaverse

no code implementations16 Dec 2022 Xinyu Zhou, Jun Zhao

The Metaverse is deemed the next evolution of the Internet and has received much attention recently.

Federated Learning object-detection +2

Generating Hierarchical Explanations on Text Classification Without Connecting Rules

no code implementations24 Oct 2022 Yiming Ju, Yuanzhe Zhang, Kang Liu, Jun Zhao

The opaqueness of deep NLP models has motivated the development of methods for interpreting how deep models predict.

text-classification Text Classification

ReasonChainQA: Text-based Complex Question Answering with Explainable Evidence Chains

no code implementations17 Oct 2022 Minjun Zhu, Yixuan Weng, Shizhu He, Kang Liu, Jun Zhao

Recently, natural language database (NLDB) conducts complex QA in knowledge base with textual evidences rather than structured representations, this task attracts a lot of attention because of the flexibility and richness of textual evidence.

Answer Generation Question Answering +1

Edge-Cloud Cooperation for DNN Inference via Reinforcement Learning and Supervised Learning

no code implementations11 Oct 2022 Tinghao Zhang, Zhijun Li, Yongrui Chen, Kwok-Yan Lam, Jun Zhao

A reinforcement learning (RL)-based DNN compression approach is used to generate the lightweight model suitable for the edge from the heavyweight model.

Image Classification object-detection +3

Time Minimization in Hierarchical Federated Learning

no code implementations7 Oct 2022 Chang Liu, Terence Jie Chua, Jun Zhao

Therefore, we formulate a joint learning and communication optimization problem to minimize total model parameter communication and computation delay, by optimizing local iteration counts and edge iteration counts.

Federated Learning

Joint Optimization of Energy Consumption and Completion Time in Federated Learning

no code implementations29 Sep 2022 Xinyu Zhou, Jun Zhao, Huimei Han, Claude Guet

Federated Learning (FL) is an intriguing distributed machine learning approach due to its privacy-preserving characteristics.

Federated Learning Privacy Preserving +1

Facial Landmark Predictions with Applications to Metaverse

1 code implementation29 Sep 2022 Qiao Han, Jun Zhao, Kwok-Yan Lam

This research aims to make metaverse characters more realistic by adding lip animations learnt from videos in the wild.

Transfer Learning

Mobile Edge Computing, Metaverse, 6G Wireless Communications, Artificial Intelligence, and Blockchain: Survey and Their Convergence

no code implementations28 Sep 2022 Yitong Wang, Jun Zhao

Compared to cloud computing, as the distributed and closer infrastructure, the convergence of MEC with other emerging technologies, including the Metaverse, 6G wireless communications, artificial intelligence (AI), and blockchain, also solves the problems of network resource allocation, more network load as well as latency requirements.


Resource Allocation and Resolution Control in the Metaverse with Mobile Augmented Reality

no code implementations28 Sep 2022 Peiyuan Si, Jun Zhao, Huimei Han, Kwok-Yan Lam, Yang Liu

With the development of blockchain and communication techniques, the Metaverse is considered as a promising next-generation Internet paradigm, which enables the connection between reality and the virtual world.

Resource Allocation for Mobile Metaverse with the Internet of Vehicles over 6G Wireless Communications: A Deep Reinforcement Learning Approach

no code implementations27 Sep 2022 Terence Jie Chua, Wenhan Yu, Jun Zhao

Being able to access scenes and information associated with the physical world, in the Metaverse in real-time and under mobility, is essential in developing a highly accessible, interactive and interconnective experience for all users.

Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder

1 code implementation COLING 2022 Fangyu Lei, Shizhu He, Xiang Li, Jun Zhao, Kang Liu

In the real-world question answering scenarios, hybrid form combining both tabular and textual contents has attracted more and more attention, among which numerical reasoning problem is one of the most typical and challenging problems.

Models Alignment Question Answering

$\textbf{P$^2$A}$: A Dataset and Benchmark for Dense Action Detection from Table Tennis Match Broadcasting Videos

no code implementations26 Jul 2022 Jiang Bian, Qingzhong Wang, Haoyi Xiong, Jun Huang, Chen Liu, Xuhong LI, Jun Cheng, Jun Zhao, Feixiang Lu, Dejing Dou

While deep learning has been widely used for video analytics, such as video classification and action detection, dense action detection with fast-moving subjects from sports videos is still challenging.

Action Detection Action Localization +2

LingYi: Medical Conversational Question Answering System based on Multi-modal Knowledge Graphs

1 code implementation20 Apr 2022 Fei Xia, Bin Li, Yixuan Weng, Shizhu He, Kang Liu, Bin Sun, Shutao Li, Jun Zhao

The medical conversational system can relieve the burden of doctors and improve the efficiency of healthcare, especially during the pandemic.

Conversational Question Answering Dialogue Generation +3

Robust PCA Unrolling Network for Super-resolution Vessel Extraction in X-ray Coronary Angiography

no code implementations16 Apr 2022 Binjie Qin, Haohao Mao, Yiming Liu, Jun Zhao, Yisong Lv, Yueqi Zhu, Song Ding, Xu Chen

Although robust PCA has been increasingly adopted to extract vessels from X-ray coronary angiography (XCA) images, challenging problems such as inefficient vessel-sparsity modelling, noisy and dynamic background artefacts, and high computational cost still remain unsolved.

feature selection Rolling Shutter Correction +1

Towards Efficiently Evaluating the Robustness of Deep Neural Networks in IoT Systems: A GAN-based Method

no code implementations19 Nov 2021 Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex Kot

Through extensive experiments, AI-GAN achieves high attack success rates, outperforming existing methods, and reduces generation time significantly.

Optimizing the Age of Information in RIS-aided SWIPT Networks

no code implementations14 Nov 2021 Wanting Lyu, Yue Xiu, Jun Zhao, Zhongpei Zhang

In this letter, a reconfigurable intelligent surface (RIS)-assisted simultaneous wireless information and power transfer (SWIPT) network is investigated.


Adversarial Purification through Representation Disentanglement

no code implementations15 Oct 2021 Tao Bai, Jun Zhao, Lanqing Guo, Bihan Wen

Deep learning models are vulnerable to adversarial examples and make incomprehensible mistakes, which puts a threat on their real-world deployment.


A Relation-Oriented Clustering Method for Open Relation Extraction

1 code implementation EMNLP 2021 Jun Zhao, Tao Gui, Qi Zhang, Yaqian Zhou

The clustering-based unsupervised relation discovery method has gradually become one of the important methods of open relation extraction (OpenRE).

Relation Extraction

Logic Traps in Evaluating Attribution Scores

no code implementations ACL 2022 Yiming Ju, Yuanzhe Zhang, Zhao Yang, Zhongtao Jiang, Kang Liu, Jun Zhao

Meanwhile, since the reasoning process of deep models is inaccessible, researchers design various evaluation methods to demonstrate their arguments.

Lifelong Intent Detection via Multi-Strategy Rebalancing

no code implementations10 Aug 2021 Qingbin Liu, Xiaoyan Yu, Shizhu He, Kang Liu, Jun Zhao

In this paper, we propose Lifelong Intent Detection (LID), which continually trains an ID model on new data to learn newly emerging intents while avoiding catastrophically forgetting old data.

Intent Detection Knowledge Distillation

Document-level Event Extraction via Parallel Prediction Networks

2 code implementations ACL 2021 Hang Yang, Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang

We argue that sentence-level extractors are ill-suited to the DEE task where event arguments always scatter across sentences and multiple events may co-exist in a document.

Document-level Event Extraction Event Extraction

Knowledge-Enriched Event Causality Identification via Latent Structure Induction Networks

no code implementations ACL 2021 Pengfei Cao, Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao, Yuguang Chen, Weihua Peng

Specifically, to make use of the descriptive knowledge, we devise a Descriptive Graph Induction module to obtain and encode the graph-structured descriptive knowledge.

Event Causality Identification

A Large-Scale Chinese Multimodal NER Dataset with Speech Clues

1 code implementation ACL 2021 Dianbo Sui, Zhengkun Tian, Yubo Chen, Kang Liu, Jun Zhao

In this paper, we aim to explore an uncharted territory, which is Chinese multimodal named entity recognition (NER) with both textual and acoustic contents.

named-entity-recognition Named Entity Recognition +1

Alignment Rationale for Natural Language Inference

no code implementations ACL 2021 Zhongtao Jiang, Yuanzhe Zhang, Zhao Yang, Jun Zhao, Kang Liu

Deep learning models have achieved great success on the task of Natural Language Inference (NLI), though only a few attempts try to explain their behaviors.

feature selection Natural Language Inference

CogIE: An Information Extraction Toolkit for Bridging Texts and CogNet

1 code implementation ACL 2021 Zhuoran Jin, Yubo Chen, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Jun Zhao

CogNet is a knowledge base that integrates three types of knowledge: linguistic knowledge, world knowledge and commonsense knowledge.

Entity Linking Entity Typing +6

Economic Dispatch of an Integrated Microgrid Based on the Dynamic Process of CCGT Plant

no code implementations5 Jul 2021 Zhiyi Lin, Chunyue Song, Jun Zhao, Chao Yang, Huan Yin

Intra-day economic dispatch of an integrated microgrid is a fundamental requirement to integrate distributed generators.

energy management Management

Inconspicuous Adversarial Patches for Fooling Image Recognition Systems on Mobile Devices

no code implementations29 Jun 2021 Tao Bai, Jinqi Luo, Jun Zhao

The patches are encouraged to be consistent with the background images with adversarial training while preserving strong attack abilities.

MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

no code implementations23 Jun 2021 Chen Liu, Bo Li, Jun Zhao, Ming Su, Xu-Dong Liu

In this paper, we propose MG-DVD, a novel detection framework based on dynamic heterogeneous graph learning, to detect malware variants in real time.

Graph Learning

LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification

no code implementations ACL 2021 Xinyu Zuo, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Weihua Peng, Yuguang Chen

On the other hand, our approach employs a dual mechanism, which is a learnable augmentation framework and can interactively adjust the generation process to generate task-related sentences.

Data Augmentation Event Causality Identification

Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion

no code implementations27 May 2021 Yinyu Lan, Shizhu He, Xiangrong Zeng, Shengping Liu, Kang Liu, Jun Zhao

To address the above issues, this paper proposes two novel path-based reasoning methods to solve the sparsity issues of entity and path respectively, which adopts the textual semantic information of entities and paths for MedKGC.

CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge

no code implementations3 Mar 2021 Chenhao Wang, Yubo Chen, Zhipeng Xue, Yang Zhou, Jun Zhao

In this paper, we present CogNet, a knowledge base (KB) dedicated to integrating three types of knowledge: (1) linguistic knowledge from FrameNet, which schematically describes situations, objects and events.

Recent Advances in Adversarial Training for Adversarial Robustness

no code implementations2 Feb 2021 Tao Bai, Jinqi Luo, Jun Zhao, Bihan Wen, Qian Wang

Adversarial training is one of the most effective approaches defending against adversarial examples for deep learning models.

Adversarial Robustness

Joint Transmit Precoding and Reflect Beamforming Design for IRS-Assisted MIMO Cognitive Radio Systems

no code implementations2 Feb 2021 Weiheng Jiang, Yu Zhang, Jun Zhao, Zehui Xiong, Zhiguo Ding

Cognitive radio (CR) is an effective solution to improve the spectral efficiency (SE) of wireless communications by allowing the secondary users (SUs) to share spectrum with primary users (PUs).

Information Theory Signal Processing Information Theory

Spectrum Sharing for 6G Integrated Satellite-Terrestrial Communication Networks Based on NOMA and Cognitive Radio

no code implementations27 Jan 2021 Xin Liu, Kwok-Yan Lam, Feng Li, Jun Zhao, Li Wang

ISTCN aims to provide high speed and pervasive network services by integrating broadband terrestrial mobile networks with satellite communication networks.


Smart City Enabled by 5G/6G Networks: An Intelligent Hybrid Random Access Scheme

no code implementations16 Jan 2021 Huimei Han, Wenchao Zhai, Jun Zhao

mMTC and URLLC will co-exist in MTC networks for 5G 6G-enabled smart city.

Sum-Rate Maximization for UAV-assisted Visible Light Communications using NOMA: Swarm Intelligence meets Machine Learning

no code implementations10 Jan 2021 Quoc-Viet Pham, Thien Huynh-The, Mamoun Alazab, Jun Zhao, Won-Joo Hwang

As the integration of unmanned aerial vehicles (UAVs) into visible light communications (VLC) can offer many benefits for massive-connectivity applications and services in 5G and beyond, this work considers a UAV-assisted VLC using non-orthogonal multiple-access.

BIG-bench Machine Learning


no code implementations1 Jan 2021 Xuanli He, Lingjuan Lyu, Lichao Sun, Xiaojun Chang, Jun Zhao

We then demonstrate how the extracted model can be exploited to develop effective attribute inference attack to expose sensitive information of the training data.

Inference Attack Model extraction +3

ANL: Anti-Noise Learning for Cross-Domain Person Re-Identification

no code implementations27 Dec 2020 Hongliang Zhang, Shoudong Han, Xiaofeng Pan, Jun Zhao

Usually, attributed to the domain gaps, the pre-trained source domain model cannot extract appropriate target domain features, which will dramatically affect the clustering performance and the accuracy of pseudo-labels.

Contrastive Learning Person Re-Identification

An LSTM-Aided Hybrid Random Access Scheme for 6G Machine Type Communication Networks

no code implementations25 Dec 2020 Wenchao Zhai, Huimei Han, Lei Liu, Jun Zhao

In this paper, an LSTM-aided hybrid random access scheme (LSTMH-RA) is proposed to support diverse quality of service (QoS) requirements in 6G machine-type communication (MTC) networks, where massive MTC (mMTC) devices and ultra-reliable low latency communications (URLLC) devices coexist.

Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning

no code implementations23 Dec 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, Massimo Tornatore, Stefano Secci

Aiming to enhance the communication performance against smart jammer, an optimization problem for jointly optimizing power allocation at the base station (BS) and reflecting beamforming at the IRS is formulated.

reinforcement-learning Reinforcement Learning (RL)

A Comprehensive Survey of 6G Wireless Communications

no code implementations21 Dec 2020 Yang Zhao, Wenchao Zhai, Jun Zhao, Tinghao Zhang, Sumei Sun, Dusit Niyato, Kwok-Yan Lam

First, we give an overview of 6G from perspectives of technologies, security and privacy, and applications.

Resource Allocation for Intelligent Reflecting Surface Aided Cooperative Communications

no code implementations18 Dec 2020 Yulan Gao, Chao Yong, Zehui Xiong, Dusit Niyato, Yue Xiao, Jun Zhao

This paper investigates an intelligent reflecting surface (IRS) aided cooperative communication network, where the IRS exploits large reflecting elements to proactively steer the incident radio-frequency wave towards destination terminals (DTs).

Privacy and Robustness in Federated Learning: Attacks and Defenses

no code implementations7 Dec 2020 Lingjuan Lyu, Han Yu, Xingjun Ma, Chen Chen, Lichao Sun, Jun Zhao, Qiang Yang, Philip S. Yu

Besides training powerful global models, it is of paramount importance to design FL systems that have privacy guarantees and are resistant to different types of adversaries.

Federated Learning Privacy Preserving

Graph-Based Knowledge Integration for Question Answering over Dialogue

no code implementations COLING 2020 Jian Liu, Dianbo Sui, Kang Liu, Jun Zhao

Despite many advances, existing approaches for this task did not consider dialogue structure and background knowledge (e. g., relationships between speakers).

Machine Reading Comprehension Question Answering +1

Privacy-Preserving Federated Learning for UAV-Enabled Networks: Learning-Based Joint Scheduling and Resource Management

no code implementations28 Nov 2020 Helin Yang, Jun Zhao, Zehui Xiong, Kwok-Yan Lam, Sumei Sun, Liang Xiao

However, due to the privacy concerns of devices and limited computation or communication resource of UAVs, it is impractical to send raw data of devices to UAV servers for model training.

Distributed Computing Federated Learning +3

Uplink Achievable Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave Systems with Resolution-Adaptive ADCs

no code implementations27 Nov 2020 Yue Xiu, Jun Zhao, Ertugrul Basar, Marco Di Renzo, Wei Sun, Guan Gui, Ning Wei

In this letter, we investigate the uplink of a reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) multi-user system.


Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSI

no code implementations22 Nov 2020 Yang Liu, Jun Zhao, Ming Li, Qingqing Wu

In this paper, we consider the weighted sum-power minimization under quality-of-service (QoS) constraints in the multi-user multi-input-single-output (MISO) uplink wireless network assisted by intelligent reflecting surface (IRS).

Field-Tuned Quantum Effects in a Triangular-Lattice Ising Magnet

no code implementations18 Nov 2020 Yayuan Qin, Yao Shen, ChangLe Liu, Hongliang Wo, Yonghao Gao, Yu Feng, Xiaowen Zhang, Gaofeng Ding, Yiqing Gu, Qisi Wang, Shoudong Shen, Helen C. Walker, Robert Bewley, Jianhui Xu, Martin Boehm, Paul Steffens, Seiko Ohira-Kawamura, Naoki Murai, Astrid Schneidewind, Xin Tong, Gang Chen, Jun Zhao

We report thermodynamic and neutron scattering measurements of the triangular-lattice quantum Ising magnet TmMgGaO 4 in longitudinal magnetic fields.

Strongly Correlated Electrons Materials Science

Joint Entity and Relation Extraction with Set Prediction Networks

1 code implementation3 Nov 2020 Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Xiangrong Zeng, Shengping Liu

Compared with cross-entropy loss that highly penalizes small shifts in triple order, the proposed bipartite matching loss is invariant to any permutation of predictions; thus, it can provide the proposed networks with a more accurate training signal by ignoring triple order and focusing on relation types and entities.

Joint Entity and Relation Extraction

Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks

no code implementations3 Nov 2020 Tao Bai, Jinqi Luo, Jun Zhao

Adversarial examples are inevitable on the road of pervasive applications of deep neural networks (DNN).

Adversarial Robustness

KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision

no code implementations COLING 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

Modern models of event causality detection (ECD) are mainly based on supervised learning from small hand-labeled corpora.

Data Augmentation

Secure Weighted Aggregation for Federated Learning

no code implementations17 Oct 2020 Jiale Guo, Ziyao Liu, Kwok-Yan Lam, Jun Zhao, Yiqiang Chen, Chaoping Xing

The situation is exacerbated by the cloud-based implementation of digital services when user data are captured and stored in distributed locations, hence aggregation of the user data for ML could be a serious breach of privacy regulations.

Cryptography and Security Distributed, Parallel, and Cluster Computing

Secrecy Rate Maximization for Reconfigurable Intelligent Surface Aided Millimeter Wave System with Low-resolution DAC

no code implementations9 Oct 2020 Yue Xiu, Jun Zhao, Zhongpei Zhang

In this letter, we investigate the secrecy rate of an reconfigurable intelligent surface (RIS)-aided millimeter-wave (mmWave) system with hardware limitations.

FTN: Foreground-Guided Texture-Focused Person Re-Identification

no code implementations24 Sep 2020 Donghaisheng Liu, Shoudong Han, Yang Chen, Chenfei Xia, Jun Zhao

Person re-identification (Re-ID) is a challenging task as persons are often in different backgrounds.

Person Re-Identification

Towards Causal Explanation Detection with Pyramid Salient-Aware Network

no code implementations CCL 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

PSAN can assist in causal explanation detection via capturing the salient semantics of discourses contained in their keywords with a bottom graph-based word-level salient network.

Event Coreference Resolution via a Multi-loss Neural Network without Using Argument Information

no code implementations22 Sep 2020 Xinyu Zuo, Yubo Chen, Kang Liu, Jun Zhao

Event coreference resolution(ECR) is an important task in Natural Language Processing (NLP) and nearly all the existing approaches to this task rely on event argument information.

coreference-resolution Coreference Resolution +2

Generating Adversarial yet Inconspicuous Patches with a Single Image

no code implementations21 Sep 2020 Jinqi Luo, Tao Bai, Jun Zhao

Through extensive experiments, our ap-proach shows strong attacking ability in both the white-box and black-box setting.

Feature Distillation With Guided Adversarial Contrastive Learning

no code implementations21 Sep 2020 Tao Bai, Jinnan Chen, Jun Zhao, Bihan Wen, Xudong Jiang, Alex Kot

In this paper, we propose a novel approach called Guided Adversarial Contrastive Distillation (GACD), to effectively transfer adversarial robustness from teacher to student with features.

Adversarial Robustness Contrastive Learning

MAT: Motion-Aware Multi-Object Tracking

no code implementations10 Sep 2020 Shoudong Han, Piao Huang, Hongwei Wang, En Yu, Donghaisheng Liu, Xiaofeng Pan, Jun Zhao

Modern multi-object tracking (MOT) systems usually model the trajectories by associating per-frame detections.

Multi-Object Tracking

Local Differential Privacy and Its Applications: A Comprehensive Survey

no code implementations9 Aug 2020 Mengmeng Yang, Lingjuan Lyu, Jun Zhao, Tianqing Zhu, Kwok-Yan Lam

Local differential privacy (LDP), as a strong privacy tool, has been widely deployed in the real world in recent years.

Cryptography and Security

Secrecy Rate Maximization for Intelligent Reflecting Surface Aided SWIPT Systems

no code implementations22 Jul 2020 Wei Sun, Qingyang Song, Lei Guo, Jun Zhao

Simultaneous wireless information and power transfer (SWIPT) and intelligent reflecting surface (IRS) are two promising techniques for providing enhanced wireless communication capability and sustainable energy supply to energy-constrained wireless devices.

A novel random access scheme for M2M communication in crowded asynchronous massive MIMO systems

no code implementations13 Jul 2020 Huimei Han, Wenchao Zhai, Zhefu Wu, Ying Li, Jun Zhao, Mingda Chen

Simulation results show that, compared to the exiting random access scheme for the crowded asynchronous massive MIMO systems, the proposed scheme can improve the uplink throughput and estimate the effective timing offsets accurately at the same time.

Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSI

no code implementations3 Jul 2020 Yang Liu, Jun Zhao, Ming Li, Qingqing Wu

In this paper, we consider the weighted sum-power minimization under quality-of-service (QoS) constraints in the multi-user multi-input-single-output (MISO) uplink wireless network assisted by intelligent reflecting surface (IRS).

Secure Beamforming for Multiple Intelligent Reflecting Surfaces Aided mmWave Systems

no code implementations26 Jun 2020 Yue Xiu, Jun Zhao, Chau Yuen, Zhongpei Zhang, Guan Gui

In this system, the secrecy rate is maximized by controlling the on-off status of each IRS as well as optimizing the phase shift matrix of the IRSs.

Attacks to Federated Learning: Responsive Web User Interface to Recover Training Data from User Gradients

no code implementations8 Jun 2020 Hans Albert Lianto, Yang Zhao, Jun Zhao

In a case where the aggregator is untrusted and LDP is not applied to each user gradient, the aggregator can recover sensitive user data from these gradients.

Federated Learning

Observed mobility behavior data reveal social distancing inertia

no code implementations30 Apr 2020 Sepehr Ghader, Jun Zhao, Minha Lee, Weiyi Zhou, Guangchen Zhao, Lei Zhang

The study revealed that statistics related to social distancing, namely trip rate, miles traveled per person, and percentage of population staying at home have all showed an unexpected trend, which we named social distancing inertia.

Computers and Society

Local Differential Privacy based Federated Learning for Internet of Things

no code implementations19 Apr 2020 Yang Zhao, Jun Zhao, Mengmeng Yang, Teng Wang, Ning Wang, Lingjuan Lyu, Dusit Niyato, Kwok-Yan Lam

To avoid the privacy threat and reduce the communication cost, in this paper, we propose to integrate federated learning and local differential privacy (LDP) to facilitate the crowdsourcing applications to achieve the machine learning model.

BIG-bench Machine Learning Federated Learning +1

Refinements in Motion and Appearance for Online Multi-Object Tracking

no code implementations16 Mar 2020 Piao Huang, Shoudong Han, Jun Zhao, Donghaisheng Liu, Hongwei Wang, En Yu, Alex ChiChung Kot

Modern multi-object tracking (MOT) system usually involves separated modules, such as motion model for location and appearance model for data association.

Multi-Object Tracking Online Multi-Object Tracking

Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications

no code implementations27 Feb 2020 Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Liang Xiao, Qingqing Wu

As the system is highly dynamic and complex, and it is challenging to address the non-convex optimization problem, a novel deep reinforcement learning (DRL)-based secure beamforming approach is firstly proposed to achieve the optimal beamforming policy against eavesdroppers in dynamic environments.

reinforcement-learning Reinforcement Learning (RL)

Residual-Sparse Fuzzy $C$-Means Clustering Incorporating Morphological Reconstruction and Wavelet frames

no code implementations14 Feb 2020 Cong Wang, Witold Pedrycz, Zhiwu Li, Mengchu Zhou, Jun Zhao

To further enhance the segmentation effects of the improved FCM algorithm, we also employ the morphological reconstruction to smoothen the labels generated by clustering.

Image Segmentation Semantic Segmentation

Poisson Kernel Avoiding Self-Smoothing in Graph Convolutional Networks

no code implementations7 Feb 2020 Ziqing Yang, Shoudong Han, Jun Zhao

Graph convolutional network (GCN) is now an effective tool to deal with non-Euclidean data, such as social networks in social behavior analysis, molecular structure analysis in the field of chemistry, and skeleton-based action recognition.

Action Recognition Skeleton Based Action Recognition

AI-GAN: Attack-Inspired Generation of Adversarial Examples

1 code implementation6 Feb 2020 Tao Bai, Jun Zhao, Jinlin Zhu, Shoudong Han, Jiefeng Chen, Bo Li, Alex Kot

Deep neural networks (DNNs) are vulnerable to adversarial examples, which are crafted by adding imperceptible perturbations to inputs.

An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning

no code implementations19 Dec 2019 Zhiying Xu, Shuyu Shi, Alex X. Liu, Jun Zhao, Lin Chen

ADADP significantly reduces the privacy cost by improving the convergence speed with an adaptive learning rate and mitigates the negative effect of differential privacy upon the model accuracy by introducing adaptive noise.

Reconfigurable Intelligent Surface Aided Power Control for Physical-Layer Broadcasting

no code implementations7 Dec 2019 Huimei Han, Jun Zhao, Zehui Xiong, Dusit Niyato, Wenchao Zhai, Marco Di Renzo, Quoc-Viet Pham, Weidang Lu

Our goalis to minimize the transmit power at the BS by jointly designing the transmit beamforming at the BSand the phase shifts of the passive elements at the RIS.

Reviewing and Improving the Gaussian Mechanism for Differential Privacy

no code implementations27 Nov 2019 Jun Zhao, Teng Wang, Tao Bai, Kwok-Yan Lam, Zhiying Xu, Shuyu Shi, Xuebin Ren, Xinyu Yang, Yang Liu, Han Yu

Although both classical Gaussian mechanisms [1, 2] assume $0 < \epsilon \leq 1$, our review finds that many studies in the literature have used the classical Gaussian mechanisms under values of $\epsilon$ and $\delta$ where the added noise amounts of [1, 2] do not achieve $(\epsilon,\delta)$-DP.

Blockchain for Future Smart Grid: A Comprehensive Survey

1 code implementation8 Nov 2019 Muhammad Baqer Mollah, Jun Zhao, Dusit Niyato, Kwok-Yan Lam, Xin Zhang, Amer M. Y. M. Ghias, Leong Hai Koh, Lei Yang

In this paper, we aim to provide a comprehensive survey on application of blockchain in smart grid.

Cryptography and Security Distributed, Parallel, and Cluster Computing Networking and Internet Architecture Social and Information Networks Systems and Control Systems and Control

Adaptive Statistical Learning with Bayesian Differential Privacy

no code implementations2 Nov 2019 Jun Zhao

Our results in adaptive statistical learning generalize the results of Dwork et al. for i. i. d.

Holdout Set

Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots

no code implementations CONLL 2019 Cao Liu, Kang Liu, Shizhu He, Zaiqing Nie, Jun Zhao

Facing this challenge, we present a response generation model which incorporates Interlocutor-aware Contexts into Recurrent Encoder-Decoder frameworks (ICRED) for RGMPC.

Chatbot Response Generation

Resource Allocation in Mobility-Aware Federated Learning Networks: A Deep Reinforcement Learning Approach

no code implementations21 Oct 2019 Huy T. Nguyen, Nguyen Cong Luong, Jun Zhao, Chau Yuen, Dusit Niyato

However, federated learning faces the energy constraints of the workers and the high network resource cost due to the fact that a number of global model transmissions may be required to achieve the target accuracy.

Federated Learning Reinforcement Learning (RL)

A Survey of Simultaneous Localization and Mapping

no code implementations24 Aug 2019 Baichuan Huang, Jun Zhao, Jingbin Liu

The paper makes an overview in SLAM including Lidar SLAM, visual SLAM, and their fusion.

Robotics Simultaneous Localization and Mapping

Copy-Enhanced Heterogeneous Information Learning for Dialogue State Tracking

no code implementations21 Aug 2019 Qingbin Liu, Shizhu He, Kang Liu, Shengping Liu, Jun Zhao

How to integrate the semantic information of pre-defined ontology and dialogue text (heterogeneous texts) to generate unknown values and improve performance becomes a severe challenge.

Dialogue State Tracking Task-Oriented Dialogue Systems

IntentGC: a Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

1 code implementation24 Jul 2019 Jun Zhao, Zhou Zhou, Ziyu Guan, Wei Zhao, Wei Ning, Guang Qiu, Xiaofei He

In this work, we collect abundant relationships from common user behaviors and item information, and propose a novel framework named IntentGC to leverage both explicit preferences and heterogeneous relationships by graph convolutional networks.

Network Embedding

Vocabulary Pyramid Network: Multi-Pass Encoding and Decoding with Multi-Level Vocabularies for Response Generation

no code implementations ACL 2019 Cao Liu, Shizhu He, Kang Liu, Jun Zhao

To tackle the above two problems, we present a Vocabulary Pyramid Network (VPN) which is able to incorporate multi-pass encoding and decoding with multi-level vocabularies into response generation.

Response Generation

AdaNSP: Uncertainty-driven Adaptive Decoding in Neural Semantic Parsing

no code implementations ACL 2019 Xiang Zhang, Shizhu He, Kang Liu, Jun Zhao

To keep the model aware of the underlying grammar in target sequences, many constrained decoders were devised in a multi-stage paradigm, which decode to the sketches or abstract syntax trees first, and then decode to target semantic tokens.

Semantic Parsing

Collecting and Analyzing Multidimensional Data with Local Differential Privacy

no code implementations28 Jun 2019 Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao, Siu Cheung Hui, Hyejin Shin, Junbum Shin, Ge Yu

Motivated by this, we first propose novel LDP mechanisms for collecting a numeric attribute, whose accuracy is at least no worse (and usually better) than existing solutions in terms of worst-case noise variance.

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

no code implementations26 Jun 2019 Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan, Dusit Niyato, Zengxiang Li, Lingjuan Lyu, Yingbo Liu

To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data.

Edge-computing Federated Learning +1

Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas

no code implementations4 Jun 2019 Teng Wang, Jun Zhao, Han Yu, Jinyan Liu, Xinyu Yang, Xuebin Ren, Shuyu Shi

To investigate such ethical dilemmas, recent studies have adopted preference aggregation, in which each voter expresses her/his preferences over decisions for the possible ethical dilemma scenarios, and a centralized system aggregates these preferences to obtain the winning decision.

Autonomous Vehicles Decision Making +1

Fast and Exact Nearest Neighbor Search in Hamming Space on Full-Text Search Engines

no code implementations20 Feb 2019 Cun Mu, Jun Zhao, Guang Yang, Binwei Yang, Zheng Yan

A growing interest has been witnessed recently from both academia and industry in building nearest neighbor search (NNS) solutions on top of full-text search engines.

Information Retrieval Representation Learning +1

Collective Event Detection via a Hierarchical and Bias Tagging Networks with Gated Multi-level Attention Mechanisms

1 code implementation EMNLP 2018 Yubo Chen, Hang Yang, Kang Liu, Jun Zhao, Yantao Jia

Traditional approaches to the task of ACE event detection primarily regard multiple events in one sentence as independent ones and recognize them separately by using sentence-level information.

Event Detection

Event Detection via Gated Multilingual Attention Mechanism

no code implementations AAAI-18 2018 Jian Liu, Yubo Chen, Kang Liu, Jun Zhao

In specific, to alleviate data scarcity problem, we exploit the consistent information in multilingual data via context attention mechanism.

Event Detection

Pattern-revising Enhanced Simple Question Answering over Knowledge Bases

no code implementations COLING 2018 Yanchao Hao, Hao liu, Shizhu He, Kang Liu, Jun Zhao

Question Answering over Knowledge Bases (KB-QA), which automatically answer natural language questions based on the facts contained by a knowledge base, is one of the most important natural language processing (NLP) tasks.

Entity Linking Fact Selection +2

Towards Practical Visual Search Engine within Elasticsearch

no code implementations23 Jun 2018 Cun Mu, Jun Zhao, Guang Yang, Jing Zhang, Zheng Yan

In this paper, we describe our end-to-end content-based image retrieval system built upon Elasticsearch, a well-known and popular textual search engine.

Content-Based Image Retrieval Retrieval

Loss Rank Mining: A General Hard Example Mining Method for Real-time Detectors

no code implementations10 Apr 2018 Hao Yu, Zhaoning Zhang, Zheng Qin, Hao Wu, Dongsheng Li, Jun Zhao, Xicheng Lu

LRM is a general method for real-time detectors, as it utilizes the final feature map which exists in all real-time detectors to mine hard examples.

IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations

no code implementations IJCNLP 2017 Shangmin Guo, Kang Liu, Shizhu He, Cao Liu, Jun Zhao, Zhuoyu Wei

The IJCNLP-2017 Multi-choice Question Answering(MCQA) task aims at exploring the performance of current Question Answering(QA) techniques via the realworld complex questions collected from Chinese Senior High School Entrance Examination papers and CK12 website1.

Question Answering

Generating Natural Answers by Incorporating Copying and Retrieving Mechanisms in Sequence-to-Sequence Learning

no code implementations ACL 2017 Shizhu He, Cao Liu, Kang Liu, Jun Zhao

Generating answer with natural language sentence is very important in real-world question answering systems, which needs to obtain a right answer as well as a coherent natural response.

Question Answering

Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?

1 code implementation EACL 2017 Shangmin Guo, Xiangrong Zeng, Shizhu He, Kang Liu, Jun Zhao

As one of the most important test of China, Gaokao is designed to be difficult enough to distinguish the excellent high school students.

Information Retrieval Multiple-choice +3