no code implementations • COLING 2022 • Biao Hu, Zhen Huang, Minghao Hu, Ziwen Zhang, Yong Dou
Recently, Transformer has achieved great success in Chinese named entity recognition (NER) owing to its good parallelism and ability to model long-range dependencies, which utilizes self-attention to encode context.
Chinese Named Entity Recognition
named-entity-recognition
+2
1 code implementation • COLING 2022 • Zhen Huang, Zhilong Lv, Xiaoyun Han, Binyang Li, Menglong Lu, Dongsheng Li
SBAG firstly pre-trains a multi-layer perception network to capture social bot features, and then constructs multiple graph neural networks by embedding the features to model the early propagation of posts, which is further used to detect rumors.
no code implementations • 13 Nov 2023 • Zhen Huang, Yihao Li, Dong Pei, Jiapeng Zhou, Xuliang Ning, Jianlin Han, Xiaoguang Han, Xuejun Chen
Text-driven fashion synthesis and design is an extremely valuable part of artificial intelligence generative content(AIGC), which has the potential to propel a tremendous revolution in the traditional fashion industry.
no code implementations • 16 Oct 2023 • Zhihong Lei, Ernest Pusateri, Shiyi Han, Leo Liu, MingBin Xu, Tim Ng, Ruchir Travadi, Youyuan Zhang, Mirko Hannemann, Man-Hung Siu, Zhen Huang
Recent advances in deep learning and automatic speech recognition have improved the accuracy of end-to-end speech recognition systems, but recognition of personal content such as contact names remains a challenge.
no code implementations • 10 Oct 2023 • Zhihong Lei, MingBin Xu, Shiyi Han, Leo Liu, Zhen Huang, Tim Ng, Yuanyuan Zhang, Ernest Pusateri, Mirko Hannemann, Yaqiao Deng, Man-Hung Siu
Recent advances in deep learning and automatic speech recognition (ASR) have enabled the end-to-end (E2E) ASR system and boosted the accuracy to a new level.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
no code implementations • 9 Oct 2023 • Zhihua Wen, Zhiliang Tian, Wei Wu, Yuxin Yang, Yanqi Shi, Zhen Huang, Dongsheng Li
Finally, we select the most fitting chains of evidence from the evidence forest and integrate them into the generated story, thereby enhancing the narrative's complexity and credibility.
no code implementations • 5 Aug 2023 • Menglong Lu, Zhen Huang, Yunxiang Zhao, Zhiliang Tian, Yang Liu, Dongsheng Li
To this end, we employ domain adversarial learning as a heuristic neural network initialization method, which can help the meta-learning module converge to a better optimal.
no code implementations • 4 Aug 2023 • Menglong Lu, Zhen Huang, Zhiliang Tian, Yunxiang Zhao, Xuanyu Fei, Dongsheng Li
Theoretically, we prove the convergence of the meta-learning algorithm in MTEM and analyze the effectiveness of MTEM in achieving domain adaptation.
no code implementations • 7 May 2023 • Zhen Huang, Han Li, Shitong Shao, Heqin Zhu, Huijie Hu, Zhiwei Cheng, Jianji Wang, S. Kevin Zhou
The pelvis, the lower part of the trunk, supports and balances the trunk.
1 code implementation • 26 Apr 2023 • Shitong Shao, Xiaohan Yuan, Zhen Huang, Ziming Qiu, Shuai Wang, Kevin Zhou
Based on this insight, we propose an approach called DiffuseExpand for expanding datasets for 2D medical image segmentation using DPM, which first samples a variety of masks from Gaussian noise to ensure the diversity, and then synthesizes images to ensure the alignment of images and masks.
no code implementations • 10 Apr 2023 • Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, Yong Dou
In the inductive setting where test TKGs contain emerging entities, the latest methods are based on symbolic rules or pre-trained language models (PLMs).
no code implementations • 10 Apr 2023 • Hanwen Du, Huanhuan Yuan, Zhen Huang, Pengpeng Zhao, Xiaofang Zhou
Generative models, such as Variational Auto-Encoder (VAE) and Generative Adversarial Network (GAN), have been successfully applied in sequential recommendation.
no code implementations • 11 Feb 2023 • Zhongwu Chen, Chengjin Xu, Fenglong Su, Zhen Huang, You Dou
Different from KGs and TKGs in the transductive setting, constantly emerging entities and relations in incomplete TKGs create demand to predict missing facts with unseen components, which is the extrapolation setting.
no code implementations • 11 Dec 2022 • Shitong Shao, Huanran Chen, Zhen Huang, Linrui Gong, Shuai Wang, Xinxiao wu
To be specific, we design a neural network-based data augmentation module with priori bias, which assists in finding what meets the teacher's strengths but the student's weaknesses, by learning magnitudes and probabilities to generate suitable data samples.
1 code implementation • 22 Oct 2022 • Hao Wang, Yixin Cao, Yangguang Li, Zhen Huang, Kun Wang, Jing Shao
Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothesis and premise documents.
no code implementations • 17 Oct 2022 • Adnan Haider, Tim Ng, Zhen Huang, Xingyu Na, Antti Veikko Rosti
Maximum mutual information (MMI) has become one of the two de facto methods for sequence-level training of speech recognition acoustic models.
1 code implementation • COLING 2022 • Hao Wang, Yangguang Li, Zhen Huang, Yong Dou
Then we integrate the multi-view contextual information to encode the evidence sentences to handle the task.
1 code implementation • 11 Jun 2022 • Wei Li, Qiming Zhang, Jing Zhang, Zhen Huang, Xinmei Tian, DaCheng Tao
To address these issues, we establish a new high-quality dataset named RealRain-1k, consisting of $1, 120$ high-resolution paired clean and rainy images with low- and high-density rain streaks, respectively.
no code implementations • 20 Jan 2022 • Rong Liang, Tiehua Zhang, Yujie Lu, Yuze Liu, Zhen Huang, Xin Chen
Specifically, we collect a sheer number of source codes (both Java and Python) from the Alipay code repository and incorporate both syntactic and semantic code knowledge into our model through the help of code parsers, in which AST information of the source codes can be interpreted and integrated.
1 code implementation • 16 Jan 2022 • Hao Wang, Yangguang Li, Zhen Huang, Yong Dou, Lingpeng Kong, Jing Shao
To alleviate feature suppression, we propose contrastive learning for unsupervised sentence embedding with soft negative samples (SNCSE).
no code implementations • 27 Aug 2021 • Zhen Huang, Xiaodan Zhuang, Daben Liu, Xiaoqiang Xiao, Yuchen Zhang, Sabato Marco Siniscalchi
To achieve such an ambitious goal, new mechanisms for foreign pronunciation generation and language model (LM) enrichment have been devised.
1 code implementation • CVPR 2021 • Zhen Huang, Xu Shen, Jun Xing, Tongliang Liu, Xinmei Tian, Houqiang Li, Bing Deng, Jianqiang Huang, Xian-Sheng Hua
The inheritance part is learned with a similarity loss to transfer the existing learned knowledge from the teacher model to the student model, while the exploration part is encouraged to learn representations different from the inherited ones with a dis-similarity loss.
1 code implementation • CVPR 2022 • Xin Jin, Tianyu He, Kecheng Zheng, Zhiheng Yin, Xu Shen, Zhen Huang, Ruoyu Feng, Jianqiang Huang, Xian-Sheng Hua, Zhibo Chen
Specifically, we introduce Gait recognition as an auxiliary task to drive the Image ReID model to learn cloth-agnostic representations by leveraging personal unique and cloth-independent gait information, we name this framework as GI-ReID.
Ranked #5 on
Person Re-Identification
on PRCC
1 code implementation • ICCV 2021 • Zhen Huang, Dixiu Xue, Xu Shen, Xinmei Tian, Houqiang Li, Jianqiang Huang, Xian-Sheng Hua
Second, different body parts possess different scales, and even the same part in different frames can appear at different locations and scales.
Ranked #2 on
Gait Recognition
on OUMVLP
no code implementations • COLING 2020 • Huibin Ruan, Yu Hong, Yang Xu, Zhen Huang, Guodong Zhou, Min Zhang
We tackle implicit discourse relation recognition.
no code implementations • COLING 2020 • Hao Wang, Zhen Huang, Yong Dou, Yu Hong
Recent research mainly models the task as a sequence tagging problem and deal with all the argumentation components at word level.
no code implementations • COLING 2020 • Xiao Li, Yu Hong, Huibin Ruan, Zhen Huang
We tackle implicit discourse relation classification, a task of automatically determining semantic relationships between arguments.
1 code implementation • 26 Nov 2020 • Zhen Huang, Xu Shen, Xinmei Tian, Houqiang Li, Jianqiang Huang, Xian-Sheng Hua
The topology of the adjacency graph is a key factor for modeling the correlations of the input skeletons.
no code implementations • 10 Jul 2020 • Owen G. Ward, Zhen Huang, Andrew Davison, Tian Zheng
Embedding nodes of a large network into a metric (e. g., Euclidean) space has become an area of active research in statistical machine learning, which has found applications in natural and social sciences.
no code implementations • 3 Jun 2020 • Zhi Shiuh Lim, Changjian Li, Zhen Huang, Xiao Chi, Jun Zhou, Shengwei Zeng, Ganesh Ji Omar, Yuan Ping Feng, Andrivo Rusydi, Stephen John Pennycook, Thirumalai Venkatesan, Ariando Ariando
Here, the emergence, tuning and interpretation of hump-shape Hall Effect from a CaMnO3/CaIrO3/CaMnO3 trilayer structure are studied in detail.
Mesoscale and Nanoscale Physics
no code implementations • 10 Nov 2019 • Wei Zhang, Youyuan Lin, Ruoran Ren, Xiaodong Wang, Zhenshuang Liang, Zhen Huang
We present the detailed mathematical construction of our method.
no code implementations • 7 Nov 2019 • Wei Zhang, Feifei Lin, Xiaodong Wang, Zhenshuang Liang, Zhen Huang
However, when the translation task involves Chinese, semantic granularity remains at the word and character level, so there is still need more fine-grained translation model of Chinese.
no code implementations • 4 Oct 2019 • Zhen Huang, Tim Ng, Leo Liu, Henry Mason, Xiaodan Zhuang, Daben Liu
The most popular way to train very deep CNNs is to use shortcut connections (SC) together with batch normalization (BN).
1 code implementation • IJCNLP 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
Rapid progress has been made in the field of reading comprehension and question answering, where several systems have achieved human parity in some simplified settings.
Ranked #8 on
Question Answering
on DROP Test
1 code implementation • ACL 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
This paper considers the reading comprehension task in which multiple documents are given as input.
1 code implementation • ACL 2019 • Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li, Yiwei Lv
Open-domain targeted sentiment analysis aims to detect opinion targets along with their sentiment polarities from a sentence.
Aspect-Based Sentiment Analysis (ABSA)
Aspect Term Extraction and Sentiment Classification
+1
no code implementations • EMNLP 2018 • Minghao Hu, Yuxing Peng, Furu Wei, Zhen Huang, Dongsheng Li, Nan Yang, Ming Zhou
Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of numerous models.
no code implementations • 17 Aug 2018 • Minghao Hu, Furu Wei, Yuxing Peng, Zhen Huang, Nan Yang, Dongsheng Li
Machine reading comprehension with unanswerable questions aims to abstain from answering when no answer can be inferred.
Ranked #11 on
Question Answering
on SQuAD2.0 dev
no code implementations • 19 May 2018 • Xiang Ao, Yang Liu, Zhen Huang, Luo Zuo, Qing He
An effective technique for filtering free-rider episodes is using a partition model to divide an episode into two consecutive subepisodes and comparing the observed support of such episode with its expected support under the assumption that these two subepisodes occur independently.
no code implementations • 2 Nov 2017 • Zhen Huang, David Lie
However, a recent study found that a significant amount of configuration errors require fixing more than one setting together.
no code implementations • 2 Nov 2017 • Dhaval Miyani, Zhen Huang, David Lie
Enforcing open source licenses such as the GNU General Public License (GPL), analyzing a binary for possible vulnerabilities, and code maintenance are all situations where it is useful to be able to determine the source code provenance of a binary.
Cryptography and Security D.4.6
3 code implementations • 8 May 2017 • Minghao Hu, Yuxing Peng, Zhen Huang, Xipeng Qiu, Furu Wei, Ming Zhou
In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects.
Ranked #17 on
Question Answering
on SQuAD1.1 dev
no code implementations • 21 Mar 2017 • Yong Xu, Jun Du, Zhen Huang, Li-Rong Dai, Chin-Hui Lee
We propose a multi-objective framework to learn both secondary targets not directly related to the intended task of speech enhancement (SE) and the primary target of the clean log-power spectra (LPS) features to be used directly for constructing the enhanced speech signals.
Sound
no code implementations • 6 Mar 2015 • Zhen Huang, Sabato Marco Siniscalchi, I-Fan Chen, Jiadong Wu, Chin-Hui Lee
We present a Bayesian approach to adapting parameters of a well-trained context-dependent, deep-neural-network, hidden Markov model (CD-DNN-HMM) to improve automatic speech recognition performance.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
no code implementations • 1 Feb 2015 • Zhijun Chen, Chaozhong Wu, Yishi Zhang, Zhen Huang, Bin Ran, Ming Zhong, Nengchao Lyu
Feature selection has attracted significant attention in data mining and machine learning in the past decades.