1 code implementation • ACL 2022 • Zhuoran Jin, Tianyi Men, Hongbang Yuan, Zhitao He, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Yubo Chen, Jun Zhao
Designing CogKGE aims to provide a unified programming framework for KGE tasks and a series of knowledge representations for downstream tasks.
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 • 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 • 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.
1 code implementation • SemEval (NAACL) 2022 • Fei Xia, Bin Li, Yixuan Weng, Shizhu He, Bin Sun, Shutao Li, Kang Liu, Jun Zhao
For the classification sub-task, we adopt the DeBERTa-v3 pre-trained model for fine-tuning datasets of different languages.
no code implementations • Findings (ACL) 2022 • Guirong Bai, Shizhu He, Kang Liu, Jun Zhao
We first formulate incremental learning for medical intent detection.
no code implementations • CCL 2020 • Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao
Specifically, to reduce the errors of predicting entity boundaries, we propose an adaptive multi-pass memory network to exploit lexical knowledge.
Chinese Named Entity Recognition named-entity-recognition +3
no code implementations • EMNLP 2021 • Yiming Ju, Yuanzhe Zhang, Zhixing Tian, Kang Liu, Xiaohuan Cao, Wenting Zhao, Jinlong Li, Jun Zhao
Multiple-choice MRC is one of the most studied tasks in MRC due to the convenience of evaluation and the flexibility of answer format.
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.
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.
1 code implementation • EMNLP 2021 • Qingbin Liu, Pengfei Cao, Cao Liu, Jiansong Chen, Xunliang Cai, Fan Yang, Shizhu He, Kang Liu, Jun Zhao
This paradigm is often impractical in real-world applications since online dialogue systems usually involve continually emerging new data and domains.
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.
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.
no code implementations • COLING 2022 • Xiusheng Huang, Hang Yang, Yubo Chen, Jun Zhao, Kang Liu, Weijian Sun, Zuyu Zhao
Document-level relation extraction aims to recognize relations among multiple entity pairs from a whole piece of article.
no code implementations • COLING 2022 • Ran Song, Shizhu He, Suncong Zheng, Shengxiang Gao, Kang Liu, Zhengtao Yu, Jun Zhao
In fact, the semantics of a relation can be expressed by three kinds of graphs: factual graph, ontology graph, textual description graph, and they can complement each other.
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.
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.
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.
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.
no code implementations • NAACL (SMM4H) 2021 • Tong Zhou, Zhucong Li, Zhen Gan, Baoli Zhang, Yubo Chen, Kun Niu, Jing Wan, Kang Liu, Jun Zhao, Yafei Shi, Weifeng Chong, Shengping Liu
This is the system description of the CASIA_Unisound team for Task 1, Task 7b, and Task 8 of the sixth Social Media Mining for Health Applications (SMM4H) shared task in 2021.
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.
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.
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.
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.
1 code implementation • 23 Apr 2024 • Yao Xu, Shizhu He, Jiabei Chen, ZiHao Wang, Yangqiu Song, Hanghang Tong, Kang Liu, Jun Zhao
To simulate real-world scenarios and evaluate the ability of LLMs to integrate internal and external knowledge, in this paper, we propose leveraging LLMs for QA under Incomplete Knowledge Graph (IKGQA), where the given KG doesn't include all the factual triples involved in each question.
1 code implementation • 1 Apr 2024 • wei he, Shichun Liu, Jun Zhao, Yiwen Ding, Yi Lu, Zhiheng Xi, Tao Gui, Qi Zhang, Xuanjing Huang
The generated demos strategically interpolate between existing demos and the given query, transforming the query from OOD to ID.
no code implementations • 30 Mar 2024 • Renyang Liu, Kwok-Yan Lam, Wei Zhou, Sixing Wu, Jun Zhao, Dongting Hu, Mingming Gong
Many attack techniques have been proposed to explore the vulnerability of DNNs and further help to improve their robustness.
1 code implementation • 26 Mar 2024 • Chenlong Zhang, Pengfei Cao, Yubo Chen, Kang Liu, Zhiqiang Zhang, Mengshu Sun, Jun Zhao
The CFED task is challenging as it involves memorizing previous event types and learning new event types with few-shot samples.
no code implementations • 25 Mar 2024 • Ziheng Deng, Hua Chen, Haibo Hu, Zhiyong Xu, Tianling Lyu, Yan Xi, Yang Chen, Jun Zhao
In this paper, we first explore the origin and appearance of streak artifacts in 4D CBCT images. Specifically, we find that streak artifacts exhibit a periodic rotational motion along with the patient's respiration.
1 code implementation • 22 Mar 2024 • Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Kang Liu, Shengping Liu, Jun Zhao
Retrieval-Augmented-Generation and Gener-ation-Augmented-Generation have been proposed to enhance the knowledge required for question answering over Large Language Models (LLMs).
no code implementations • 12 Mar 2024 • Rui Zhao, Jun Zhao
We believe this work demonstrates a practicality of a perennial DToU language and the potential of a paradigm shift to how users interact with data and applications in a decentralized Web, offering both improved privacy and usability.
no code implementations • 9 Mar 2024 • Wangtao Sun, Haotian Xu, Xuanqing Yu, Pei Chen, Shizhu He, Jun Zhao, Kang Liu
Although Large Language Models (LLMs) are showing impressive performance on a wide range of Natural Language Processing tasks, researchers have found that they still have limited ability to conduct induction.
no code implementations • 8 Mar 2024 • Wangtao Sun, Shizhu He, Jun Zhao, Kang Liu
With good explanatory power and controllability, rule-based methods play an important role in many tasks such as knowledge reasoning and decision support.
1 code implementation • 5 Mar 2024 • Zhitao He, Pengfei Cao, Chenhao Wang, Zhuoran Jin, Yubo Chen, Jiexin Xu, Huaijun Li, XiaoJian Jiang, Kang Liu, Jun Zhao
In this paper, (1) we introduce SimuCourt, a judicial benchmark that encompasses 420 judgment documents from real-world, spanning the three most common types of judicial cases, and a novel task Judicial Decision-Making to evaluate the judicial analysis and decision-making power of agents.
no code implementations • 5 Mar 2024 • Zhitao He, Pengfei Cao, Zhuoran Jin, Yubo Chen, Kang Liu, Zhiqiang Zhang, Mengshu Sun, Jun Zhao
Event Causality Identification (ECI) refers to the detection of causal relations between events in texts.
no code implementations • 29 Feb 2024 • Hongbang Yuan, Pengfei Cao, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao
Large Language Models (LLMs) have shown impressive capabilities but still suffer from the issue of hallucinations.
no code implementations • 28 Feb 2024 • Jiachun Li, Pengfei Cao, Chenhao Wang, Zhuoran Jin, Yubo Chen, Daojian Zeng, Kang Liu, Jun Zhao
Large language models exhibit high-level commonsense reasoning abilities, especially with enhancement methods like Chain-of-Thought (CoT).
no code implementations • 28 Feb 2024 • Zhuoran Jin, Pengfei Cao, Hongbang Yuan, Yubo Chen, Jiexin Xu, Huaijun Li, XiaoJian Jiang, Kang Liu, Jun Zhao
Moreover, we reveal that the pivotal point at which knowledge conflicts emerge in LMs is the integration of inconsistent information flows by memory heads and context heads.
no code implementations • 22 Feb 2024 • Zhihao Zhang, Jun Zhao, Qi Zhang, Tao Gui, Xuanjing Huang
Furthermore, this core region exhibits significant dimensional dependency, perturbations to even a single parameter on specific dimensions leading to a loss of linguistic competence.
no code implementations • 22 Feb 2024 • Zhuoran Jin, Pengfei Cao, Yubo Chen, Kang Liu, XiaoJian Jiang, Jiexin Xu, Qiuxia Li, Jun Zhao
Then, we investigate the behavior and preference of RALMs from the following two perspectives: (1) Conflicts between internal memory and external sources: We find that stronger RALMs emerge with the Dunning-Kruger effect, persistently favoring their faulty internal memory even when correct evidence is provided.
no code implementations • 21 Feb 2024 • YuHeng Chen, Pengfei Cao, Yubo Chen, Yining Wang, Shengping Liu, Kang Liu, Jun Zhao
This paper provides a comprehensive definition of DKNs that covers both structural and functional aspects, pioneering the study of structures in PLMs' factual knowledge storage units.
1 code implementation • 20 Feb 2024 • Tongxu Luo, Jiahe Lei, Fangyu Lei, Weihao Liu, Shizhu He, Jun Zhao, Kang Liu
Fine-tuning is often necessary to enhance the adaptability of Large Language Models (LLM) to downstream tasks.
no code implementations • 19 Feb 2024 • Xiaowei Yuan, Zhao Yang, Yequan Wang, Shengping Liu, Jun Zhao, Kang Liu
Large language models internalize enormous parametric knowledge during pre-training.
1 code implementation • 18 Feb 2024 • Jun Zhao, Can Zu, Hao Xu, Yi Lu, wei he, Yiwen Ding, Tao Gui, Qi Zhang, Xuanjing Huang
Large language models (LLMs) have demonstrated impressive performance in understanding language and executing complex reasoning tasks.
no code implementations • 18 Feb 2024 • Nuo Xu, Jun Zhao, Can Zu, Sixian Li, Lu Chen, Zhihao Zhang, Rui Zheng, Shihan Dou, Wenjuan Qin, Tao Gui, Qi Zhang, Xuanjing Huang
To address this issue, we propose a cost-effective preference learning strategy, optimizing reward models by distinguishing between human and machine translations.
1 code implementation • 16 Feb 2024 • Yi Lu, Xin Zhou, wei he, Jun Zhao, Tao Ji, Tao Gui, Qi Zhang, Xuanjing Huang
Instead of allowing each head to attend to the full sentence, which struggles with generalizing to longer sequences due to out-of-distribution (OOD) issues, we allow each head to process in-distribution length by selecting and attending to important context chunks.
no code implementations • 16 Feb 2024 • Chenhui Hu, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao
Knowledge editing aims to rectify inaccuracies in large language models (LLMs) without costly retraining for outdated or erroneous knowledge.
no code implementations • 15 Feb 2024 • Jiaxiang Liu, Tong Zhou, Yubo Chen, Kang Liu, Jun Zhao
In summary, our results pave the way for enhancing LLMs by incorporating Pseudo- and Multisource-KGs, particularly in the context of open-ended questions.
1 code implementation • 15 Feb 2024 • Yixuan Weng, Shizhu He, Kang Liu, Shengping Liu, Jun Zhao
This heightens the need to control model behaviors.
no code implementations • 14 Feb 2024 • Zhao Li, Xin Wang, JianXin Li, Wenbin Guo, Jun Zhao
Existing knowledge hypergraph embedding methods mainly focused on improving model performance, but their model structures are becoming more complex and redundant.
no code implementations • 4 Feb 2024 • Tinghao Zhang, Kwok-Yan Lam, Jun Zhao
For scalability, practical HFL schemes select a subset of IoT devices to participate in the training, hence the notion of device scheduling.
no code implementations • 3 Feb 2024 • Jianing He, Qi Zhang, Weiping Ding, Duoqian Miao, Jun Zhao, Liang Hu, Longbing Cao
DE$^3$-BERT implements a hybrid exiting strategy that supplements classic entropy-based local information with distance-based global information to enhance the estimation of prediction correctness for more reliable early exiting decisions.
no code implementations • 25 Jan 2024 • Mohamed R. Shoaib, Heba M. Emara, Jun Zhao, Walid El-Shafai, Naglaa F. Soliman, Ahmed S. Mubarak, Osama A. Omer, Fathi E. Abd El-Samie, Hamada Esmaiel
The InceptionResNetv2 model, incorporating transfer learning, registered an impressive 97. 5% accuracy in both the training and testing phases.
no code implementations • 12 Jan 2024 • Mohamed R. Shoaib, Heba M. Emara, Jun Zhao
This survey paper explores the transformative influence of frontier AI, foundation models, and Large Language Models (LLMs) in the realm of Intelligent Transportation Systems (ITS), emphasizing their integral role in advancing transportation intelligence, optimizing traffic management, and contributing to the realization of smart cities.
1 code implementation • 11 Jan 2024 • Binghai Wang, Rui Zheng, Lu Chen, Yan Liu, Shihan Dou, Caishuang Huang, Wei Shen, Senjie Jin, Enyu Zhou, Chenyu Shi, Songyang Gao, Nuo Xu, Yuhao Zhou, Xiaoran Fan, Zhiheng Xi, Jun Zhao, Xiao Wang, Tao Ji, Hang Yan, Lixing Shen, Zhan Chen, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang
We introduce a series of novel methods to mitigate the influence of incorrect and ambiguous preferences in the dataset and fully leverage high-quality preference data.
no code implementations • 2 Jan 2024 • Jun Zhao, Zhihao Zhang, Luhui Gao, Qi Zhang, Tao Gui, Xuanjing Huang
In recent times, substantial advancements have been witnessed in large language models (LLMs), exemplified by ChatGPT, showcasing remarkable proficiency across a range of complex tasks.
1 code implementation • 15 Dec 2023 • Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, ShiLiang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
Supervised fine-tuning (SFT) is a crucial step for large language models (LLMs), enabling them to align with human instructions and enhance their capabilities in downstream tasks.
no code implementations • 12 Dec 2023 • Renyang Liu, Wei Zhou, Sixin Wu, Jun Zhao, Kwok-Yan Lam
Extensive studies have demonstrated that deep neural networks (DNNs) are vulnerable to adversarial attacks, which brings a huge security risk to the further application of DNNs, especially for the AI models developed in the real world.
no code implementations • 11 Dec 2023 • Yitong Wang, Chang Liu, Jun Zhao
In pursuit of enhancing the accessibility of AIGC services, the deployment of AIGC models (e. g., diffusion models) to edge servers and local devices has become a prevailing trend.
no code implementations • 11 Dec 2023 • Wenhan Yu, Terence Jie Chua, Jun Zhao
In spite of the rapid advancements in current technologies, the computation required for a smooth, seamless and immersive socialization experience in the Metaverse is overbearing, and the accumulated user experience is essential to be considered.
no code implementations • 7 Dec 2023 • Yang Li, Xinyu Zhou, Jun Zhao
The secrecy rate is the communication rate at which no information is disclosed to an eavesdropper.
1 code implementation • 21 Nov 2023 • Tong Zhou, Yubo Chen, Pengfei Cao, Kang Liu, Jun Zhao, Shengping Liu
To this end, we present a pretraining corpus curation and assessment platform called Oasis -- a one-stop system for data quality improvement and quantification with user-friendly interactive interfaces.
1 code implementation • 13 Nov 2023 • Wangtao Sun, Xuanqing Yu, Shizhu He, Jun Zhao, Kang Liu
Black-box Large Language Models (LLMs) have shown great power in solving various tasks and are considered general problem solvers.
no code implementations • 31 Oct 2023 • Mohamed R. Shoaib, Heba M. Emara, Jun Zhao
Food security, a global concern, necessitates precise and diverse data-driven solutions to address its multifaceted challenges.
no code implementations • 26 Oct 2023 • Terence Jie Chua, Wenhan Yu, Jun Zhao, Kwok-Yan Lam
FedPEAT uses adapters, emulators, and PEFT for federated model tuning, enhancing model privacy and memory efficiency.
no code implementations • 26 Oct 2023 • Wenhan Yu, Terence Jie Chua, Jun Zhao
The efficient deployment and fine-tuning of foundation models are pivotal in contemporary artificial intelligence.
2 code implementations • 23 Oct 2023 • Fangyu Lei, Qian Liu, Yiming Huang, Shizhu He, Jun Zhao, Kang Liu
The rapid development of Large Language Models (LLMs) has led to great strides in model capabilities like long-context understanding and reasoning.
no code implementations • 23 Oct 2023 • Fangyu Lei, Tongxu Luo, Pengqi Yang, Weihao Liu, Hanwen Liu, Jiahe Lei, Yiming Huang, Yifan Wei, Shizhu He, Jun Zhao, Kang Liu
Table-based question answering (TableQA) is an important task in natural language processing, which requires comprehending tables and employing various reasoning ways to answer the questions.
no code implementations • 23 Oct 2023 • Jun Zhao, Zhihao Zhang, Yide Ma, Qi Zhang, Tao Gui, Luhui Gao, Xuanjing Huang
We have discovered a core region in LLMs that corresponds to linguistic competence, accounting for approximately 1% of the total model parameters.
1 code implementation • 17 Oct 2023 • Yao Xu, Shizhu He, Cunguang Wang, Li Cai, Kang Liu, Jun Zhao
However, these methods train KG embeddings and neural set operators concurrently on both simple (one-hop) and complex (multi-hop and logical) queries, which causes performance degradation on simple queries and low training efficiency.
1 code implementation • 16 Oct 2023 • Zhongtao Jiang, Yuanzhe Zhang, Cao Liu, Jun Zhao, Kang Liu
In this paper, we for the first time theoretically and empirically identify that such a paradox is mainly due to the label shift of the in-context model to the data distribution, in which LLMs shift the label marginal $p(y)$ while having a good label conditional $p(x|y)$.
no code implementations • 15 Oct 2023 • Renyang Liu, Jinhong Zhang, Kwok-Yan Lam, Jun Zhao, Wei Zhou
However, the distribution of these fake data lacks diversity and cannot detect the decision boundary of the target model well, resulting in the dissatisfactory simulation effect.
no code implementations • 15 Oct 2023 • Renyang Liu, Jun Zhao, Xing Chu, Yu Liang, Wei Zhou, Jing He
With the rapid development of GPU (Graphics Processing Unit) technologies and neural networks, we can explore more appropriate data structures and algorithms.
no code implementations • 11 Oct 2023 • Renyang Liu, Wei Zhou, Tianwei Zhang, Kangjie Chen, Jun Zhao, Kwok-Yan Lam
Existing black-box attacks have demonstrated promising potential in creating adversarial examples (AE) to deceive deep learning models.
no code implementations • 8 Oct 2023 • Wei Shen, Rui Zheng, WenYu Zhan, Jun Zhao, Shihan Dou, Tao Gui, Qi Zhang, Xuanjing Huang
Reinforcement learning from human feedback serves as a crucial bridge, aligning large language models with human and societal values.
1 code implementation • 8 Oct 2023 • Yifan Wei, Yisong Su, Huanhuan Ma, Xiaoyan Yu, Fangyu Lei, Yuanzhe Zhang, Jun Zhao, Kang Liu
As a result, it is natural for people to believe that LLMs have also mastered abilities such as time understanding and reasoning.
no code implementations • 22 Sep 2023 • Tongxu Luo, Fangyu Lei, Jiahe Lei, Weihao Liu, Shihu He, Jun Zhao, Kang Liu
Answering numerical questions over hybrid contents from the given tables and text(TextTableQA) is a challenging task.
no code implementations • 17 Sep 2023 • Tinghao Zhang, Kwok-Yan Lam, Jun Zhao
The large population of wireless users is a key driver of data-crowdsourced Machine Learning (ML).
no code implementations • 9 Sep 2023 • Weihao Liu, Fangyu Lei, Tongxu Luo, Jiahe Lei, Shizhu He, Jun Zhao, Kang Liu
Most importantly, we propose a Type-specific In-context Learning Strategy for MMHQA, enabling LLMs to leverage their powerful performance in this task.
1 code implementation • 31 Aug 2023 • Zhongtao Jiang, Yuanzhe Zhang, Cao Liu, Jiansong Chen, Jun Zhao, Kang Liu
As the key to sentiment analysis, sentiment composition considers the classification of a constituent via classifications of its contained sub-constituents and rules operated on them.
no code implementations • 28 Aug 2023 • Baoli Zhang, Haining Xie, Pengfan Du, JunHao Chen, Pengfei Cao, Yubo Chen, Shengping Liu, Kang Liu, Jun Zhao
To this end, we propose the ZhuJiu benchmark, which has the following strengths: (1) Multi-dimensional ability coverage: We comprehensively evaluate LLMs across 7 ability dimensions covering 51 tasks.
1 code implementation • 25 Aug 2023 • YuHeng Chen, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao
We design cross-lingual knowledge editing experiments, demonstrating that the PLMs can accomplish this task based on language-independent neurons; (2) The discovery of Degenerate Knowledge Neurons, a novel type of neuron showing that different knowledge neurons can store the same fact.
1 code implementation • 20 Aug 2023 • Yixuan Weng, Zhiqi Wang, Huanxuan Liao, Shizhu He, Shengping Liu, Kang Liu, Jun Zhao
With the burgeoning development in the realm of large language models (LLMs), the demand for efficient incremental training tailored to specific industries and domains continues to increase.
no code implementations • 18 Aug 2023 • Peiyuan Si, Jun Zhao, Kwok-Yan Lam, Qing Yang
In this paper, we aim to explore the use of uplink semantic communications with the assistance of UAV in order to improve data collection effiicency for metaverse users in remote areas.
no code implementations • 18 Aug 2023 • Beichuan Zhang, Chenggen Sun, Jianchao Tan, Xinjun Cai, Jun Zhao, Mengqi Miao, Kang Yin, Chengru Song, Na Mou, Yang song
Increasing the size of embedding layers has shown to be effective in improving the performance of recommendation models, yet gradually causing their sizes to exceed terabytes in industrial recommender systems, and hence the increase of computing and storage costs.
no code implementations • 8 Aug 2023 • Wenhan Yu, Jun Zhao
Advanced video technologies are driving the development of the futuristic Metaverse, which aims to connect users from anywhere and anytime.
no code implementations • 8 Jun 2023 • Jun Zhao, Yongxin Zhang, Qi Zhang, Tao Gui, Zhongyu Wei, Minlong Peng, Mingming Sun
The key to the setting is selecting which instances to label.
1 code implementation • 8 Jun 2023 • Jun Zhao, WenYu Zhan, Xin Zhao, Qi Zhang, Tao Gui, Zhongyu Wei, Junzhe Wang, Minlong Peng, Mingming Sun
However, general matching methods lack explicit modeling of the above matching pattern.
1 code implementation • 8 Jun 2023 • Jun Zhao, Xin Zhao, WenYu Zhan, Qi Zhang, Tao Gui, Zhongyu Wei, Yunwen Chen, Xiang Gao, Xuanjing Huang
Inspired by text adversarial attacks, we adaptively apply small but critical perturbations to original training instances and thus synthesizing negative instances that are more likely to be mistaken by the model as known relations.
no code implementations • 29 May 2023 • Peiyuan Si, Liangxin Qian, Jun Zhao, Kwok-Yan Lam
Unmanned aerial vehicles (UAVs) are promising for providing communication services due to their advantages in cost and mobility, especially in the context of the emerging Metaverse and Internet of Things (IoT).
no code implementations • 23 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.
1 code implementation • 19 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.
1 code implementation • 9 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.
1 code implementation • 5 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.
3 code implementations • 4 Apr 2023 • Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Kang Liu, Jun Zhao
Our work highlights the potential of seamlessly unifying explicit rule learning via CoNNs and implicit pattern learning in LMs, paving the way for true symbolic comprehension capabilities.
no code implementations • 31 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.
no code implementations • 18 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.
no code implementations • 18 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.
no code implementations • 8 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.
no code implementations • 3 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.
no code implementations • 7 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.
no code implementations • 4 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.
no code implementations • 30 Dec 2022 • Wenhan Yu, Terence Jie Chua, Jun Zhao
In the DL stage, the larger-size 3D virtual objects need to be transmitted back to the XUs.
no code implementations • 19 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.
1 code implementation • 19 Dec 2022 • Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, Jun Zhao
By performing a backward verification of the answers that LLM deduced for itself, we can obtain interpretable answer validation scores to select the candidate answer with the highest score.
no code implementations • 16 Dec 2022 • Xinyu Zhou, Jun Zhao
The Metaverse is deemed the next evolution of the Internet and has received much attention recently.
no code implementations • 16 Nov 2022 • Xinyu Zhou, Chang Liu, Jun Zhao
The Metaverse has received much attention recently.
no code implementations • 24 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.
no code implementations • 17 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.
no code implementations • 11 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.
no code implementations • 7 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.
no code implementations • 29 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.
1 code implementation • 29 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.
no code implementations • 28 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.
no code implementations • 28 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.
no code implementations • 27 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.
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.
no code implementations • 26 Jul 2022 • Jiang Bian, Xuhong LI, Tao Wang, Qingzhong Wang, Jun Huang, Chen Liu, Jun Zhao, Feixiang Lu, Dejing Dou, Haoyi Xiong
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.
1 code implementation • 20 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.
no code implementations • 16 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.
no code implementations • 19 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.
no code implementations • 14 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.
no code implementations • 15 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.
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).
Ranked #1 on Relation Extraction on FewRel
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.
no code implementations • 10 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.
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.
1 code implementation • ACL 2021 • Tong Zhou, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Kun Niu, Weifeng Chong, Shengping Liu
The ICD coding task aims at assigning codes of the International Classification of Diseases in clinical notes.
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.
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.
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.
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.
no code implementations • 5 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.
no code implementations • 29 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.
no code implementations • 23 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.
no code implementations • Findings (ACL) 2021 • Xinyu Zuo, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Weihua Peng, Yuguang Chen
Current models for event causality identification (ECI) mainly adopt a supervised framework, which heavily rely on labeled data for training.
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.
no code implementations • 27 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.
no code implementations • EACL 2021 • Pei Chen, Kang Liu, Yubo Chen, Taifeng Wang, Jun Zhao
This paper proposes a new task regarding event reason extraction from document-level texts.
1 code implementation • ACL 2021 • Tao Gui, Xiao Wang, Qi Zhang, Qin Liu, Yicheng Zou, Xin Zhou, Rui Zheng, Chong Zhang, Qinzhuo Wu, Jiacheng Ye, Zexiong Pang, Yongxin Zhang, Zhengyan Li, Ruotian Ma, Zichu Fei, Ruijian Cai, Jun Zhao, Xingwu Hu, Zhiheng Yan, Yiding Tan, Yuan Hu, Qiyuan Bian, Zhihua Liu, Bolin Zhu, Shan Qin, Xiaoyu Xing, Jinlan Fu, Yue Zhang, Minlong Peng, Xiaoqing Zheng, Yaqian Zhou, Zhongyu Wei, Xipeng Qiu, Xuanjing Huang
To guarantee user acceptability, all the text transformations are linguistically based, and we provide a human evaluation for each one.
no code implementations • 3 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.
no code implementations • 2 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.
no code implementations • 2 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
no code implementations • 27 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.
no code implementations • 16 Jan 2021 • Huimei Han, Wenchao Zhai, Jun Zhao
mMTC and URLLC will co-exist in MTC networks for 5G 6G-enabled smart city.
no code implementations • 10 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.
no code implementations • 1 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.
no code implementations • 27 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.
no code implementations • 25 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.
no code implementations • 23 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.
no code implementations • 21 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.
no code implementations • 18 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).
no code implementations • 7 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.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Pei Chen, Hang Yang, Kang Liu, Ruihong Huang, Yubo Chen, Taifeng Wang, Jun Zhao
Event information is usually scattered across multiple sentences within a document.
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).
Ranked #6 on Question Answering on FriendsQA
no code implementations • 28 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.
no code implementations • 27 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.
no code implementations • 22 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).
no code implementations • 18 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
1 code implementation • 3 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.
Ranked #1 on Joint Entity and Relation Extraction on NYT
no code implementations • 3 Nov 2020 • Tao Bai, Jinqi Luo, Jun Zhao
Adversarial examples are inevitable on the road of pervasive applications of deep neural networks (DNN).
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.
no code implementations • 17 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
no code implementations • COLING 2020 • Guirong Bai, Shizhu He, Kang Liu, Jun Zhao, Zaiqing Nie
Active learning is able to significantly reduce the annotation cost for data-driven techniques.
no code implementations • 9 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.
no code implementations • 24 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.
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.
no code implementations • 22 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.
no code implementations • 21 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.
no code implementations • 21 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.
no code implementations • 10 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.
1 code implementation • Findings (EMNLP) 2021 • Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao
In this paper, we propose a federated denoising framework to suppress label noise in federated settings.
no code implementations • 9 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
no code implementations • 22 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.
no code implementations • 13 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.
no code implementations • 11 Jul 2020 • Yue Xiu, Jun Zhao, Wei Sun, Marco Di Renzo, Guan Gui, Zhongpei Zhang, Ning Wei
Then, we solve the power allocation problem under fixed phase shifts of the RIS and hybrid beamforming.
no code implementations • 3 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).
no code implementations • ACL 2020 • Yuanzhe Zhang, Zhongtao Jiang, Tao Zhang, Shiwan Liu, Jiarun Cao, Kang Liu, Shengping Liu, Jun Zhao
Electronic Medical Records (EMRs) have become key components of modern medical care systems.
no code implementations • ACL 2020 • Pengfei Cao, Chenwei Yan, Xiangling Fu, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu, Weifeng Chong
In this paper, we introduce Clinical-Coder, an online system aiming to assign ICD codes to Chinese clinical notes.
no code implementations • ACL 2020 • Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu, Weifeng Chong
Specifically, we propose a hyperbolic representation method to leverage the code hierarchy.
no code implementations • 26 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.
no code implementations • 8 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.
no code implementations • 30 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
no code implementations • 19 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.
no code implementations • NAACL 2021 • Dianbo Sui, Yubo Chen, Binjie Mao, Delai Qiu, Kang Liu, Jun Zhao
This is mainly due to the fact that human beings can leverage knowledge obtained from relevant tasks.
no code implementations • 16 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.
no code implementations • 9 Mar 2020 • Xianpei Han, Zhichun Wang, Jiangtao Zhang, Qinghua Wen, Wenqi Li, Buzhou Tang, Qi. Wang, Zhifan Feng, Yang Zhang, Yajuan Lu, Haitao Wang, Wenliang Chen, Hao Shao, Yubo Chen, Kang Liu, Jun Zhao, Taifeng Wang, Kezun Zhang, Meng Wang, Yinlin Jiang, Guilin Qi, Lei Zou, Sen Hu, Minhao Zhang, Yinnian Lin
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks.
no code implementations • 27 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.
no code implementations • 14 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.
no code implementations • 7 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.
no code implementations • 7 Feb 2020 • Ge Song, Jun Zhao, Xiaoyang Tan
Hashing based cross-modal retrieval has recently made significant progress.
1 code implementation • 6 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.
no code implementations • 19 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.
no code implementations • 7 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.
no code implementations • 27 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.
1 code implementation • 8 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
no code implementations • 2 Nov 2019 • Jun Zhao
Our results in adaptive statistical learning generalize the results of Dwork et al. for i. i. d.
no code implementations • IJCNLP 2019 • Jian Liu, Yubo Chen, Kang Liu, Jun Zhao
In this paper, we propose a new method for cross-lingual ED, demonstrating a minimal dependency on parallel resources.
1 code implementation • IJCNLP 2019 • Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu
The lack of word boundaries information has been seen as one of the main obstacles to develop a high performance Chinese named entity recognition (NER) system.
Ranked #11 on Chinese Named Entity Recognition on Weibo NER
Chinese Named Entity Recognition named-entity-recognition +2