Search Results for author: Min Zhang

Found 381 papers, 166 papers with code

Minimum $n$-Rank Approximation via Iterative Hard Thresholding

no code implementations18 Nov 2013 Min Zhang, Lei Yang, Zheng-Hai Huang

Additionally, combining an effective heuristic for determining $n$-rank, we can also apply the proposed algorithm to solve MnRA when $n$-rank is unknown in advance.

Image Inpainting Video Inpainting

Boost Phrase-level Polarity Labelling with Review-level Sentiment Classification

no code implementations11 Feb 2015 Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma

In this paper, we focus on the problem of phrase-level sentiment polarity labelling and attempt to bridge the gap between phrase-level and review-level sentiment analysis.

Classification General Classification +2

Variational Neural Discourse Relation Recognizer

1 code implementation EMNLP 2016 Biao Zhang, Deyi Xiong, Jinsong Su, Qun Liu, Rongrong Ji, Hong Duan, Min Zhang

In order to perform efficient inference and learning, we introduce neural discourse relation models to approximate the prior and posterior distributions of the latent variable, and employ these approximated distributions to optimize a reparameterized variational lower bound.

Relation

Variational Neural Machine Translation

1 code implementation EMNLP 2016 Biao Zhang, Deyi Xiong, Jinsong Su, Hong Duan, Min Zhang

Models of neural machine translation are often from a discriminative family of encoderdecoders that learn a conditional distribution of a target sentence given a source sentence.

Machine Translation Sentence +1

Word Segmentation on Micro-blog Texts with External Lexicon and Heterogeneous Data

no code implementations4 Aug 2016 Qingrong Xia, Zhenghua Li, Jiayuan Chao, Min Zhang

This paper describes our system designed for the NLPCC 2016 shared task on word segmentation on micro-blog texts.

Segmentation

Training Dependency Parsers with Partial Annotation

no code implementations29 Sep 2016 Zhenghua Li, Yue Zhang, Jiayuan Chao, Min Zhang

The first approach is previously proposed to directly train a log-linear graph-based parser (LLGPar) with PA based on a forest-based objective.

Dependency Parsing

Neural Machine Translation Advised by Statistical Machine Translation

no code implementations17 Oct 2016 Xing Wang, Zhengdong Lu, Zhaopeng Tu, Hang Li, Deyi Xiong, Min Zhang

Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years.

Machine Translation NMT +1

Learning Event Expressions via Bilingual Structure Projection

no code implementations COLING 2016 Fangyuan Li, Ruihong Huang, Deyi Xiong, Min Zhang

Aiming to resolve high complexities of event descriptions, previous work (Huang and Riloff, 2013) proposes multi-faceted event recognition and a bootstrapping method to automatically acquire both event facet phrases and event expressions from unannotated texts.

Distributed Representations for Building Profiles of Users and Items from Text Reviews

no code implementations COLING 2016 Wenliang Chen, Zhenjie Zhang, Zhenghua Li, Min Zhang

In this paper, we propose an approach to learn distributed representations of users and items from text comments for recommendation systems.

Collaborative Filtering Decision Making +3

Improving Statistical Machine Translation with Selectional Preferences

no code implementations COLING 2016 Haiqing Tang, Deyi Xiong, Min Zhang, ZhengXian Gong

In this paper, we study semantic dependencies between verbs and their arguments by modeling selectional preferences in the context of machine translation.

Machine Translation Semantic Role Labeling +2

Modeling Source Syntax for Neural Machine Translation

no code implementations ACL 2017 Junhui Li, Deyi Xiong, Zhaopeng Tu, Muhua Zhu, Min Zhang, Guodong Zhou

Even though a linguistics-free sequence to sequence model in neural machine translation (NMT) has certain capability of implicitly learning syntactic information of source sentences, this paper shows that source syntax can be explicitly incorporated into NMT effectively to provide further improvements.

Machine Translation NMT +1

Multi-Grained Chinese Word Segmentation

no code implementations EMNLP 2017 Chen Gong, Zhenghua Li, Min Zhang, Xinzhou Jiang

Traditionally, word segmentation (WS) adopts the single-grained formalism, where a sentence corresponds to a single word sequence.

Chinese Word Segmentation Language Modelling +2

Improved English to Russian Translation by Neural Suffix Prediction

no code implementations11 Jan 2018 Kai Song, Yue Zhang, Min Zhang, Weihua Luo

Neural machine translation (NMT) suffers a performance deficiency when a limited vocabulary fails to cover the source or target side adequately, which happens frequently when dealing with morphologically rich languages.

Machine Translation NMT +1

SEE: Syntax-aware Entity Embedding for Neural Relation Extraction

no code implementations11 Jan 2018 Zhengqiu He, Wenliang Chen, Zhenghua Li, Meishan Zhang, Wei zhang, Min Zhang

First, we encode the context of entities on a dependency tree as sentence-level entity embedding based on tree-GRU.

Relation Relation Classification +3

Classification of lung nodules in CT images based on Wasserstein distance in differential geometry

no code implementations30 Jun 2018 Min Zhang, Qianli Ma, Chengfeng Wen, Hai Chen, Deruo Liu, Xianfeng GU, Jie He, Xiaoyin Xu

The Wasserstein distance between the nodules is calculated based on our new spherical optimal mass transport, this new algorithm works directly on sphere by using spherical metric, which is much more accurate and efficient than previous methods.

Computed Tomography (CT) General Classification +2

Report of NEWS 2018 Named Entity Transliteration Shared Task

no code implementations WS 2018 Nancy Chen, Rafael E. Banchs, Min Zhang, Xiangyu Duan, Haizhou Li

This report presents the results from the Named Entity Transliteration Shared Task conducted as part of The Seventh Named Entities Workshop (NEWS 2018) held at ACL 2018 in Melbourne, Australia.

Information Retrieval Transliteration

Supervised Treebank Conversion: Data and Approaches

no code implementations ACL 2018 Xinzhou Jiang, Zhenghua Li, Bo Zhang, Min Zhang, Sheng Li, Luo Si

Treebank conversion is a straightforward and effective way to exploit various heterogeneous treebanks for boosting parsing performance.

Dependency Parsing Multi-Task Learning +1

Adaptive Weighting for Neural Machine Translation

1 code implementation COLING 2018 Yachao Li, Junhui Li, Min Zhang

In the popular sequence to sequence (seq2seq) neural machine translation (NMT), there exist many weighted sum models (WSMs), each of which takes a set of input and generates one output.

Machine Translation NMT +1

Interpretable Convolutional Neural Networks via Feedforward Design

2 code implementations5 Oct 2018 C. -C. Jay Kuo, Min Zhang, Siyang Li, Jiali Duan, Yueru Chen

To construct convolutional layers, we develop a new signal transform, called the Saab (Subspace Approximation with Adjusted Bias) transform.

Improving the Transformer Translation Model with Document-Level Context

3 code implementations EMNLP 2018 Jiacheng Zhang, Huanbo Luan, Maosong Sun, FeiFei Zhai, Jingfang Xu, Min Zhang, Yang Liu

Although the Transformer translation model (Vaswani et al., 2017) has achieved state-of-the-art performance in a variety of translation tasks, how to use document-level context to deal with discourse phenomena problematic for Transformer still remains a challenge.

Sentence Translation

Semi-supervised learning via Feedforward-Designed Convolutional Neural Networks

no code implementations6 Feb 2019 Yueru Chen, Yijing Yang, Min Zhang, C. -C. Jay Kuo

A semi-supervised learning framework using the feedforward-designed convolutional neural networks (FF-CNNs) is proposed for image classification in this work.

Benchmarking General Classification +1

A Novel Euler's Elastica based Segmentation Approach for Noisy Images via using the Progressive Hedging Algorithm

no code implementations20 Feb 2019 Lu Tan, Ling Li, Wanquan Liu, Jie Sun, Min Zhang

Euler's Elastica based unsupervised segmentation models have strong capability of completing the missing boundaries for existing objects in a clean image, but they are not working well for noisy images.

Segmentation

Jointly Learning Explainable Rules for Recommendation with Knowledge Graph

1 code implementation9 Mar 2019 Weizhi Ma, Min Zhang, Yue Cao, Woojeong, Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, Xiang Ren

The framework encourages two modules to complement each other in generating effective and explainable recommendation: 1) inductive rules, mined from item-centric knowledge graphs, summarize common multi-hop relational patterns for inferring different item associations and provide human-readable explanation for model prediction; 2) recommendation module can be augmented by induced rules and thus have better generalization ability dealing with the cold-start issue.

Explainable Recommendation Knowledge Graphs +1

HLT@SUDA at SemEval 2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing

no code implementations11 Mar 2019 Wei Jiang, Zhenghua Li, Yu Zhang, Min Zhang

The key idea is to convert a UCCA semantic graph into a constituent tree, in which extra labels are deliberately designed to mark remote edges and discontinuous nodes for future recovery.

General Classification UCCA Parsing

Jointly Learning Structured Analysis Discriminative Dictionary and Analysis Multiclass Classifier

no code implementations27 May 2019 Zhao Zhang, Weiming Jiang, Jie Qin, Li Zhang, Fanzhang Li, Min Zhang, Shuicheng Yan

Then we compute a linear classifier based on the approximated sparse codes by an analysis mechanism to simultaneously consider the classification and representation powers.

Dictionary Learning General Classification

HLT@SUDA at SemEval-2019 Task 1: UCCA Graph Parsing as Constituent Tree Parsing

no code implementations SEMEVAL 2019 Wei Jiang, Zhenghua Li, Yu Zhang, Min Zhang

The key idea is to convert a UCCA semantic graph into a constituent tree, in which extra labels are deliberately designed to mark remote edges and discontinuous nodes for future recovery.

General Classification Multi-Task Learning +1

Zero-Shot Cross-Lingual Abstractive Sentence Summarization through Teaching Generation and Attention

1 code implementation ACL 2019 Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, Weihua Luo

But there is no cross-lingual parallel corpus, whose source sentence language is different to the summary language, to directly train a cross-lingual ASSUM system.

Sentence Sentence Summarization +1

Aspect Sentiment Classification Towards Question-Answering with Reinforced Bidirectional Attention Network

no code implementations ACL 2019 Jingjing Wang, Changlong Sun, Shoushan Li, Xiaozhong Liu, Luo Si, Min Zhang, Guodong Zhou

This paper extends the research to interactive reviews and proposes a new research task, namely Aspect Sentiment Classification towards Question-Answering (ASC-QA), for real-world applications.

General Classification Question Answering +2

Sentence-Level Agreement for Neural Machine Translation

no code implementations ACL 2019 Mingming Yang, Rui Wang, Kehai Chen, Masao Utiyama, Eiichiro Sumita, Min Zhang, Tiejun Zhao

The training objective of neural machine translation (NMT) is to minimize the loss between the words in the translated sentences and those in the references.

Machine Translation NMT +2

Semi-supervised Domain Adaptation for Dependency Parsing

1 code implementation ACL 2019 Zhenghua Li, Xue Peng, Min Zhang, Rui Wang, Luo Si

During the past decades, due to the lack of sufficient labeled data, most studies on cross-domain parsing focus on unsupervised domain adaptation, assuming there is no target-domain training data.

Chinese Dependency Parsing Dependency Parsing +3

Syntax-aware Neural Semantic Role Labeling

1 code implementation22 Jul 2019 Qingrong Xia, Zhenghua Li, Min Zhang, Meishan Zhang, Guohong Fu, Rui Wang, Luo Si

Semantic role labeling (SRL), also known as shallow semantic parsing, is an important yet challenging task in NLP.

Semantic Parsing Semantic Role Labeling +1

PointHop: An Explainable Machine Learning Method for Point Cloud Classification

3 code implementations30 Jul 2019 Min Zhang, Haoxuan You, Pranav Kadam, Shan Liu, C. -C. Jay Kuo

In the attribute building stage, we address the problem of unordered point cloud data using a space partitioning procedure and developing a robust descriptor that characterizes the relationship between a point and its one-hop neighbor in a PointHop unit.

Attribute BIG-bench Machine Learning +3

Emotion Detection with Neural Personal Discrimination

no code implementations IJCNLP 2019 Xiabing Zhou, Zhongqing Wang, Shoushan Li, Guodong Zhou, Min Zhang

Accordingly, we propose a Neural Personal Discrimination (NPD) approach to address above challenges by determining personal attributes from posts, and connecting relevant posts with similar attributes to jointly learn their emotions.

CCKS 2019 Shared Task on Inter-Personal Relationship Extraction

1 code implementation29 Aug 2019 Haitao Wang, Zhengqiu He, Tong Zhu, Hao Shao, Wenliang Chen, Min Zhang

In this paper, we present the task definition, the description of data and the evaluation methodology used during this shared task.

Sentence

Modeling Graph Structure in Transformer for Better AMR-to-Text Generation

1 code implementation IJCNLP 2019 Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, Guodong Zhou

Recent studies on AMR-to-text generation often formalize the task as a sequence-to-sequence (seq2seq) learning problem by converting an Abstract Meaning Representation (AMR) graph into a word sequence.

AMR-to-Text Generation Text Generation

Neural Logic Networks

no code implementations17 Oct 2019 Shaoyun Shi, Hanxiong Chen, Min Zhang, Yongfeng Zhang

The fundamental idea behind the design of most neural networks is to learn similarity patterns from data for prediction and inference, which lacks the ability of logical reasoning.

Collaborative Filtering Logical Reasoning

Contrastive Attention Mechanism for Abstractive Sentence Summarization

1 code implementation IJCNLP 2019 Xiangyu Duan, Hoongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang

We propose a contrastive attention mechanism to extend the sequence-to-sequence framework for abstractive sentence summarization task, which aims to generate a brief summary of a given source sentence.

Abstractive Text Summarization Sentence +1

Robust Triple-Matrix-Recovery-Based Auto-Weighted Label Propagation for Classification

no code implementations20 Nov 2019 Huan Zhang, Zhao Zhang, Mingbo Zhao, Qiaolin Ye, Min Zhang, Meng Wang

Our method can jointly re-cover the underlying clean data, clean labels and clean weighting spaces by decomposing the original data, predicted soft labels or weights into a clean part plus an error part by fitting noise.

General Classification

Improving Neural Relation Extraction with Positive and Unlabeled Learning

no code implementations28 Nov 2019 Zhengqiu He, Wenliang Chen, Yuyi Wang, Wei zhang, Guanchun Wang, Min Zhang

We present a novel approach to improve the performance of distant supervision relation extraction with Positive and Unlabeled (PU) Learning.

reinforcement-learning Reinforcement Learning (RL) +3

Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation

no code implementations3 Dec 2019 Baijun Ji, Zhirui Zhang, Xiangyu Duan, Min Zhang, Boxing Chen, Weihua Luo

However, existing transfer methods involving a common target language are far from success in the extreme scenario of zero-shot translation, due to the language space mismatch problem between transferor (the parent model) and transferee (the child model) on the source side.

Machine Translation NMT +2

Knowledge Graph Embedding via Graph Attenuated Attention Networks

no code implementations IEEE Access 2019 Rui Wang, Bicheng Li, Shengwei Hu, Wenqian Du, Min Zhang

However, these methods assign the same weights on the relation path in the knowledge graph and ignore the rich information presented in neighbor nodes, which result in incomplete mining of triple features.

Knowledge Base Completion Knowledge Graph Embedding +4

AE-OT-GAN: Training GANs from data specific latent distribution

no code implementations ECCV 2020 Dongsheng An, Yang Guo, Min Zhang, Xin Qi, Na lei, Shing-Tung Yau, Xianfeng GU

Though generative adversarial networks (GANs) areprominent models to generate realistic and crisp images, they often encounter the mode collapse problems and arehard to train, which comes from approximating the intrinsicdiscontinuous distribution transform map with continuousDNNs.

Stochastic Item Descent Method for Large Scale Equal Circle Packing Problem

no code implementations22 Jan 2020 Kun He, Min Zhang, Jianrong Zhou, Yan Jin, Chu-min Li

Inspired by its success in deep learning, we apply the idea of SGD with batch selection of samples to a classic optimization problem in decision version.

PointHop++: A Lightweight Learning Model on Point Sets for 3D Classification

2 code implementations9 Feb 2020 Min Zhang, Yifan Wang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo

The PointHop method was recently proposed by Zhang et al. for 3D point cloud classification with unsupervised feature extraction.

3D Classification 3D Point Cloud Classification +2

Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?

1 code implementation6 Mar 2020 Houquan Zhou, Yu Zhang, Zhenghua Li, Min Zhang

In the pre deep learning era, part-of-speech tags have been considered as indispensable ingredients for feature engineering in dependency parsing.

Dependency Parsing Feature Engineering +4

Efficient Second-Order TreeCRF for Neural Dependency Parsing

2 code implementations ACL 2020 Yu Zhang, Zhenghua Li, Min Zhang

Experiments and analysis on 27 datasets from 13 languages clearly show that techniques developed before the DL era, such as structural learning (global TreeCRF loss) and high-order modeling are still useful, and can further boost parsing performance over the state-of-the-art biaffine parser, especially for partially annotated training data.

Chinese Dependency Parsing Dependency Parsing

RepBERT: Contextualized Text Embeddings for First-Stage Retrieval

3 code implementations28 Jun 2020 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

Although exact term match between queries and documents is the dominant method to perform first-stage retrieval, we propose a different approach, called RepBERT, to represent documents and queries with fixed-length contextualized embeddings.

Passage Ranking Retrieval

Aspect Sentiment Classification with Document-level Sentiment Preference Modeling

no code implementations ACL 2020 Xiao Chen, Changlong Sun, Jingjing Wang, Shoushan Li, Luo Si, Min Zhang, Guodong Zhou

This justifies the importance of the document-level sentiment preference information to ASC and the effectiveness of our approach capturing such information.

Classification General Classification +4

Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation

2 code implementations1 Jul 2020 Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma

However, existing KG enhanced recommendation methods have largely focused on exploring advanced neural network architectures to better investigate the structural information of KG.

Knowledge Graph Embedding Knowledge Graphs +2

Syntax-Aware Opinion Role Labeling with Dependency Graph Convolutional Networks

no code implementations ACL 2020 Bo Zhang, Yue Zhang, Rui Wang, Zhenghua Li, Min Zhang

The experimental results show that syntactic information is highly valuable for ORL, and our final MTL model effectively boosts the F1 score by 9. 29 over the syntax-agnostic baseline.

Fine-Grained Opinion Analysis Multi-Task Learning

Bilingual Dictionary Based Neural Machine Translation without Using Parallel Sentences

1 code implementation ACL 2020 Xiangyu Duan, Baijun Ji, Hao Jia, Min Tan, Min Zhang, Boxing Chen, Weihua Luo, Yue Zhang

In this paper, we propose a new task of machine translation (MT), which is based on no parallel sentences but can refer to a ground-truth bilingual dictionary.

Machine Translation Translation +1

Accelerating Robustness Verification of Deep Neural Networks Guided by Target Labels

no code implementations16 Jul 2020 Wenjie Wan, Zhaodi Zhang, Yiwei Zhu, Min Zhang, Fu Song

The key insight of our approach is that the robustness verification problem of DNNs can be solved by verifying sub-problems of DNNs, one per target label.

Autonomous Driving Medical Diagnosis

Neural Logic Reasoning

3 code implementations20 Aug 2020 Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang, Yongfeng Zhang

Both reasoning and generalization ability are important for prediction tasks such as recommender systems, where reasoning provides strong connection between user history and target items for accurate prediction, and generalization helps the model to draw a robust user portrait over noisy inputs.

Logical Reasoning Recommendation Systems

Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)

no code implementations2 Sep 2020 Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo

An unsupervised point cloud registration method, called salient points analysis (SPA), is proposed in this work.

Point Cloud Registration Single Particle Analysis

Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation

no code implementations2 Sep 2020 Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo

The UFF method exploits statistical correlations of points in a point cloud set to learn shape and point features in a one-pass feedforward manner through a cascaded encoder-decoder architecture.

Classification General Classification +2

Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition

1 code implementation10 Sep 2020 Siteng Huang, Min Zhang, Yachen Kang, Donglin Wang

However, these approaches only augment the representations of samples with available semantics while ignoring the query set, which loses the potential for the improvement and may lead to a shift between the modalities combination and the pure-visual representation.

feature selection Metric Learning

A new dataset of dog breed images and a benchmark for fine-grained classification

1 code implementation1 Oct 2020 Ding-Nan Zo, Song-Hai Zhang, Tai-Jiang M, Min Zhang

It is currently the largest dataset for fine-grained classification of dogs, including130 dog breeds and 70, 428 real-world images.

Benchmarking Classification +3

Improving AMR Parsing with Sequence-to-Sequence Pre-training

1 code implementation EMNLP 2020 Dongqin Xu, Junhui Li, Muhua Zhu, Min Zhang, Guodong Zhou

In the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser with good performance.

Ranked #15 on AMR Parsing on LDC2017T10 (using extra training data)

AMR Parsing Machine Translation +1

Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization

no code implementations17 Oct 2020 Min Zhang, Yao Shu, Kun He

Finite-sum optimization plays an important role in the area of machine learning, and hence has triggered a surge of interest in recent years.

Learning To Retrieve: How to Train a Dense Retrieval Model Effectively and Efficiently

2 code implementations20 Oct 2020 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, Shaoping Ma

Through this process, it teaches the DR model how to retrieve relevant documents from the entire corpus instead of how to rerank a potentially biased sample of documents.

Passage Retrieval Retrieval

Towards Accurate and Consistent Evaluation: A Dataset for Distantly-Supervised Relation Extraction

1 code implementation COLING 2020 Tong Zhu, Haitao Wang, Junjie Yu, Xiabing Zhou, Wenliang Chen, Wei zhang, Min Zhang

The experimental results show that the ranking lists of the comparison systems on the DS-labelled test data and human-annotated test data are different.

Relation Relation Extraction

Loss re-scaling VQA: Revisiting the LanguagePrior Problem from a Class-imbalance View

1 code implementation30 Oct 2020 Yangyang Guo, Liqiang Nie, Zhiyong Cheng, Qi Tian, Min Zhang

Concretely, we design a novel interpretation scheme whereby the loss of mis-predicted frequent and sparse answers of the same question type is distinctly exhibited during the late training phase.

Face Recognition Image Classification +2

Improving Relation Extraction with Relational Paraphrase Sentences

1 code implementation COLING 2020 Junjie Yu, Tong Zhu, Wenliang Chen, Wei zhang, Min Zhang

In this paper, we propose an alternative approach to improve RE systems via enriching diverse expressions by relational paraphrase sentences.

Relation Relation Extraction

Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations

no code implementations COLING 2020 Ying Li, Zhenghua Li, Min Zhang

The major challenge for current parsing research is to improve parsing performance on out-of-domain texts that are very different from the in-domain training data when there is only a small-scale out-domain labeled data.

Dependency Parsing Domain Adaptation +2

Multi-grained Chinese Word Segmentation with Weakly Labeled Data

no code implementations COLING 2020 Chen Gong, Zhenghua Li, Bowei Zou, Min Zhang

Detailed evaluation shows that our proposed model with weakly labeled data significantly outperforms the state-of-the-art MWS model by 1. 12 and 5. 97 on NEWS and BAIKE data in F1.

Chinese Word Segmentation Sentence

Semantic Role Labeling with Heterogeneous Syntactic Knowledge

1 code implementation COLING 2020 Qingrong Xia, Rui Wang, Zhenghua Li, Yue Zhang, Min Zhang

Recently, due to the interplay between syntax and semantics, incorporating syntactic knowledge into neural semantic role labeling (SRL) has achieved much attention.

Semantic Role Labeling

Code Summarization with Structure-induced Transformer

1 code implementation Findings (ACL) 2021 Hongqiu Wu, Hai Zhao, Min Zhang

Code summarization (CS) is becoming a promising area in recent language understanding, which aims to generate sensible human language automatically for programming language in the format of source code, serving in the most convenience of programmer developing.

Code Summarization Natural Language Understanding +1

LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document Understanding

5 code implementations ACL 2021 Yang Xu, Yiheng Xu, Tengchao Lv, Lei Cui, Furu Wei, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Wanxiang Che, Min Zhang, Lidong Zhou

Pre-training of text and layout has proved effective in a variety of visually-rich document understanding tasks due to its effective model architecture and the advantage of large-scale unlabeled scanned/digital-born documents.

Document Image Classification Document Layout Analysis +6

Cortical Surface Shape Analysis Based on Alexandrov Polyhedra

no code implementations ICCV 2021 Min Zhang, Yang Guo, Na lei, Zhou Zhao, Jianfeng Wu, Xiaoyin Xu, Yalin Wang, Xianfeng GU

Shape analysis has been playing an important role in early diagnosis and prognosis of neurodegenerative diseases such as Alzheimer's diseases (AD).

R-PointHop: A Green, Accurate, and Unsupervised Point Cloud Registration Method

1 code implementation15 Mar 2021 Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo

Inspired by the recent PointHop classification method, an unsupervised 3D point cloud registration method, called R-PointHop, is proposed in this work.

Attribute Dimensionality Reduction +2

Dialogue History Matters! Personalized Response Selectionin Multi-turn Retrieval-based Chatbots

no code implementations17 Mar 2021 Juntao Li, Chang Liu, Chongyang Tao, Zhangming Chan, Dongyan Zhao, Min Zhang, Rui Yan

To fill the gap between these up-to-date methods and the real-world applications, we incorporate user-specific dialogue history into the response selection and propose a personalized hybrid matching network (PHMN).

Representation Learning Retrieval

Not All Attention Is All You Need

no code implementations NeurIPS 2021 Hongqiu Wu, Hai Zhao, Min Zhang

Beyond the success story of pre-trained language models (PrLMs) in recent natural language processing, they are susceptible to over-fitting due to unusual large model size.

Document Classification Named Entity Recognition (NER) +1

Optimizing Dense Retrieval Model Training with Hard Negatives

4 code implementations16 Apr 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

ADORE replaces the widely-adopted static hard negative sampling method with a dynamic one to directly optimize the ranking performance.

Information Retrieval Representation Learning +1

An In-depth Study on Internal Structure of Chinese Words

1 code implementation ACL 2021 Chen Gong, Saihao Huang, Houquan Zhou, Zhenghua Li, Min Zhang, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan

Several previous works on syntactic parsing propose to annotate shallow word-internal structures for better utilizing character-level information.

Sentence

A Unified Span-Based Approach for Opinion Mining with Syntactic Constituents

1 code implementation NAACL 2021 Qingrong Xia, Bo Zhang, Rui Wang, Zhenghua Li, Yue Zhang, Fei Huang, Luo Si, Min Zhang

Fine-grained opinion mining (OM) has achieved increasing attraction in the natural language processing (NLP) community, which aims to find the opinion structures of {``}Who expressed what opinions towards what{''} in one sentence.

Multi-Task Learning Opinion Mining +1

Combining Static Word Embeddings and Contextual Representations for Bilingual Lexicon Induction

1 code implementation Findings (ACL) 2021 Jinpeng Zhang, Baijun Ji, Nini Xiao, Xiangyu Duan, Min Zhang, Yangbin Shi, Weihua Luo

Bilingual Lexicon Induction (BLI) aims to map words in one language to their translations in another, and is typically through learning linear projections to align monolingual word representation spaces.

Bilingual Lexicon Induction Word Embeddings

Learning on Abstract Domains: A New Approach for Verifiable Guarantee in Reinforcement Learning

no code implementations13 Jun 2021 Peng Jin, Min Zhang, Jianwen Li, Li Han, Xuejun Wen

Formally verifying Deep Reinforcement Learning (DRL) systems is a challenging task due to the dynamic continuity of system behaviors and the black-box feature of embedded neural networks.

reinforcement-learning Reinforcement Learning (RL)

Exploiting Rich Syntax for Better Knowledge Base Question Answering

no code implementations16 Jul 2021 Pengju Zhang, Yonghui Jia, Muhua Zhu, Wenliang Chen, Min Zhang

Previous works for encoding questions mainly focus on the word sequences, but seldom consider the information from syntactic trees. In this paper, we propose an approach to learn syntax-based representations for KBQA.

Knowledge Base Question Answering

Jointly Optimizing Query Encoder and Product Quantization to Improve Retrieval Performance

5 code implementations2 Aug 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Compared with previous DR models that use brute-force search, JPQ almost matches the best retrieval performance with 30x compression on index size.

Information Retrieval Quantization +1

Towards a Better Understanding Human Reading Comprehension with Brain Signals

1 code implementation3 Aug 2021 Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma

In this paper, we carefully design a lab-based user study to investigate brain activities during reading comprehension.

EEG Electroencephalogram (EEG) +5

Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics

no code implementations1 Sep 2021 Xiaotian Jiang, Danshi Wang, Qirui Fan, Min Zhang, Chao Lu, Alan Pak Tao Lau

A physics-informed neural network (PINN) that combines deep learning with physics is studied to solve the nonlinear Schr\"odinger equation for learning nonlinear dynamics in fiber optics.

Why Don't You Click: Neural Correlates of Non-Click Behaviors in Web Search

no code implementations22 Sep 2021 Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuancheng Li, Jiaji Li, Xuesong Chen, Min Zhang, Shaoping Ma

Inspired by these findings, we conduct supervised learning tasks to estimate the usefulness of non-click results with brain signals and conventional information (i. e., content and context factors).

EEG Electroencephalogram (EEG)

GSIP: Green Semantic Segmentation of Large-Scale Indoor Point Clouds

no code implementations24 Sep 2021 Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo

It is named GSIP (Green Segmentation of Indoor Point clouds) and its performance is evaluated on a representative large-scale benchmark -- the Stanford 3D Indoor Segmentation (S3DIS) dataset.

Segmentation Semantic Segmentation

Stochastic Variance Reduced Ensemble Adversarial Attack

no code implementations29 Sep 2021 Jiadong Lin, Yifeng Xiong, Min Zhang, John E. Hopcroft, Kun He

Black-box adversarial attack has attracted much attention for its practical use in deep learning applications, and it is very challenging as there is no access to the architecture and weights of the target model.

Adversarial Attack

Are BERT Families Zero-Shot Learners? A Study on Their Potential and Limitations

no code implementations29 Sep 2021 Yue Wang, Lijun Wu, Xiaobo Liang, Juntao Li, Min Zhang

Starting from the resurgence of deep learning, language models (LMs) have never been so popular.

DM-CT: Consistency Training with Data and Model Perturbation

no code implementations29 Sep 2021 Xiaobo Liang, Runze Mao, Lijun Wu, Juntao Li, Weiqing Liu, Qing Li, Min Zhang

The common approach of consistency training is performed on the data-level, which typically utilizes the data augmentation strategy (or adversarial training) to make the predictions from the augmented input and the original input to be consistent, so that the model is more robust and attains better generalization ability.

Data Augmentation Image Classification +2

Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval

4 code implementations12 Oct 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

However, the efficiency of most existing DR models is limited by the large memory cost of storing dense vectors and the time-consuming nearest neighbor search (NNS) in vector space.

Constrained Clustering Information Retrieval +3

Web Search via an Efficient and Effective Brain-Machine Interface

no code implementations14 Oct 2021 Xuesong Chen, Ziyi Ye, Xiaohui Xie, Yiqun Liu, Weihang Su, Shuqi Zhu, Min Zhang, Shaoping Ma

While search technologies have evolved to be robust and ubiquitous, the fundamental interaction paradigm has remained relatively stable for decades.

EEG Electroencephalogram (EEG)

Stochastic Variance Reduced Ensemble Adversarial Attack for Boosting the Adversarial Transferability

1 code implementation CVPR 2022 Yifeng Xiong, Jiadong Lin, Min Zhang, John E. Hopcroft, Kun He

The black-box adversarial attack has attracted impressive attention for its practical use in the field of deep learning security.

Adversarial Attack

Interpreting Dense Retrieval as Mixture of Topics

no code implementations27 Nov 2021 Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

Dense Retrieval (DR) reaches state-of-the-art results in first-stage retrieval, but little is known about the mechanisms that contribute to its success.

Retrieval

Fast and Accurate End-to-End Span-based Semantic Role Labeling as Word-based Graph Parsing

1 code implementation COLING 2022 Shilin Zhou, Qingrong Xia, Zhenghua Li, Yu Zhang, Yu Hong, Min Zhang

Moreover, we propose a simple constrained Viterbi procedure to ensure the legality of the output graph according to the constraints of the SRL structure.

Chinese Word Segmentation named-entity-recognition +3

GreenPCO: An Unsupervised Lightweight Point Cloud Odometry Method

no code implementations8 Dec 2021 Pranav Kadam, Min Zhang, Jiahao Gu, Shan Liu, C. -C. Jay Kuo

GreenPCO is an unsupervised learning method that predicts object motion by matching features of consecutive point cloud scans.

Benchmarking Object +1

Efficient Document-level Event Extraction via Pseudo-Trigger-aware Pruned Complete Graph

1 code implementation11 Dec 2021 Tong Zhu, Xiaoye Qu, Wenliang Chen, Zhefeng Wang, Baoxing Huai, Nicholas Jing Yuan, Min Zhang

Most previous studies of document-level event extraction mainly focus on building argument chains in an autoregressive way, which achieves a certain success but is inefficient in both training and inference.

Document-level Event Extraction Event Extraction

Learning Semantic-Aligned Feature Representation for Text-based Person Search

1 code implementation13 Dec 2021 Shiping Li, Min Cao, Min Zhang

In this paper, we propose a semantic-aligned embedding method for text-based person search, in which the feature alignment across modalities is achieved by automatically learning the semantic-aligned visual features and textual features.

Person Search Text based Person Retrieval +1

CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation

2 code implementations13 Dec 2021 Chong Liu, Xiaoyang Liu, Rongqin Zheng, Lixin Zhang, Xiaobo Liang, Juntao Li, Lijun Wu, Min Zhang, Leyu Lin

State-of-the-art sequential recommendation models proposed very recently combine contrastive learning techniques for obtaining high-quality user representations.

Click-Through Rate Prediction Contrastive Learning +2

Self-Distillation Mixup Training for Non-autoregressive Neural Machine Translation

no code implementations22 Dec 2021 Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Yuxia Wang, Zongyao Li, Zhengzhe Yu, Zhanglin Wu, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang

An effective training strategy to improve the performance of AT models is Self-Distillation Mixup (SDM) Training, which pre-trains a model on raw data, generates distilled data by the pre-trained model itself and finally re-trains a model on the combination of raw data and distilled data.

Knowledge Distillation Machine Translation +1

A Label Dependence-aware Sequence Generation Model for Multi-level Implicit Discourse Relation Recognition

1 code implementation22 Dec 2021 Changxing Wu, Liuwen Cao, Yubin Ge, Yang Liu, Min Zhang, Jinsong Su

Then, we employ a label sequence decoder to output the predicted labels in a top-down manner, where the predicted higher-level labels are directly used to guide the label prediction at the current level.

Relation

Joint-training on Symbiosis Networks for Deep Nueral Machine Translation models

no code implementations22 Dec 2021 Zhengzhe Yu, Jiaxin Guo, Minghan Wang, Daimeng Wei, Hengchao Shang, Zongyao Li, Zhanglin Wu, Yuxia Wang, Yimeng Chen, Chang Su, Min Zhang, Lizhi Lei, Shimin Tao, Hao Yang

Deep encoders have been proven to be effective in improving neural machine translation (NMT) systems, but it reaches the upper bound of translation quality when the number of encoder layers exceeds 18.

Machine Translation NMT +1

Recommendation Unlearning

1 code implementation18 Jan 2022 Chong Chen, Fei Sun, Min Zhang, Bolin Ding

From the perspective of utility, if a system's utility is damaged by some bad data, the system needs to forget these data to regain utility.

Machine Unlearning Recommendation Systems

Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation

no code implementations ACL 2022 Chulun Zhou, Fandong Meng, Jie zhou, Min Zhang, Hongji Wang, Jinsong Su

Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner.

Knowledge Distillation Language Modelling +3

Towards Unifying the Label Space for Aspect- and Sentence-based Sentiment Analysis

1 code implementation Findings (ACL) 2022 Yiming Zhang, Min Zhang, Sai Wu, Junbo Zhao

The aspect-based sentiment analysis (ABSA) is a fine-grained task that aims to determine the sentiment polarity towards targeted aspect terms occurring in the sentence.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +3

Image-text Retrieval: A Survey on Recent Research and Development

no code implementations28 Mar 2022 Min Cao, Shiping Li, Juntao Li, Liqiang Nie, Min Zhang

On top of this, the efficiency-focused study on the ITR system is introduced as the third perspective.

Retrieval Text Retrieval

A Survey on Dropout Methods and Experimental Verification in Recommendation

no code implementations5 Apr 2022 Yangkun Li, Weizhi Ma, Chong Chen, Min Zhang, Yiqun Liu, Shaoping Ma, Yuekui Yang

Among various methods of coping with overfitting, dropout is one of the representative ways.

BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation

no code implementations16 Apr 2022 Zheng Zhang, Liang Ding, Dazhao Cheng, Xuebo Liu, Min Zhang, DaCheng Tao

Data augmentations (DA) are the cores to achieving robust sequence-to-sequence learning on various natural language processing (NLP) tasks.

Grammatical Error Correction Machine Translation +1

A Survey on Non-Autoregressive Generation for Neural Machine Translation and Beyond

1 code implementation20 Apr 2022 Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, Tie-Yan Liu

While NAR generation can significantly accelerate inference speed for machine translation, the speedup comes at the cost of sacrificed translation accuracy compared to its counterpart, autoregressive (AR) generation.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +11

Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations

1 code implementation ACL 2022 Xin Zhang, Guangwei Xu, Yueheng Sun, Meishan Zhang, Xiaobin Wang, Min Zhang

Recent works of opinion expression identification (OEI) rely heavily on the quality and scale of the manually-constructed training corpus, which could be extremely difficult to satisfy.

MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction

2 code implementations NAACL 2022 Yue Zhang, Zhenghua Li, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, Min Zhang

This paper presents MuCGEC, a multi-reference multi-source evaluation dataset for Chinese Grammatical Error Correction (CGEC), consisting of 7, 063 sentences collected from three Chinese-as-a-Second-Language (CSL) learner sources.

Grammatical Error Correction Sentence

Evaluating Interpolation and Extrapolation Performance of Neural Retrieval Models

1 code implementation25 Apr 2022 Jingtao Zhan, Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma

For example, representation-based retrieval models perform almost as well as interaction-based retrieval models in terms of interpolation but not extrapolation.

Retrieval

Language Anisotropic Cross-Lingual Model Editing

1 code implementation25 May 2022 Yang Xu, Yutai Hou, Wanxiang Che, Min Zhang

On the newly defined cross-lingual model editing task, we empirically demonstrate the failure of monolingual baselines in propagating the edit to multiple languages and the effectiveness of the proposed language anisotropic model editing.

Model Editing

Neural Network Verification with Proof Production

no code implementations1 Jun 2022 Omri Isac, Clark Barrett, Min Zhang, Guy Katz

In this work, we present a novel mechanism for enhancing Simplex-based DNN verifiers with proof production capabilities: the generation of an easy-to-check witness of unsatisfiability, which attests to the absence of errors.

Collision Avoidance LEMMA

A Survey on the Fairness of Recommender Systems

no code implementations8 Jun 2022 Yifan Wang, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma

First, we summarize fairness definitions in the recommendation and provide several views to classify fairness issues.

Fairness Recommendation Systems

Medical Dialogue Response Generation with Pivotal Information Recalling

no code implementations17 Jun 2022 Yu Zhao, Yunxin Li, Yuxiang Wu, Baotian Hu, Qingcai Chen, Xiaolong Wang, Yuxin Ding, Min Zhang

To mitigate this problem, we propose a medical response generation model with Pivotal Information Recalling (MedPIR), which is built on two components, i. e., knowledge-aware dialogue graph encoder and recall-enhanced generator.

Dialogue Generation Graph Attention +1

Adversarial Self-Attention for Language Understanding

1 code implementation25 Jun 2022 Hongqiu Wu, Ruixue Ding, Hai Zhao, Pengjun Xie, Fei Huang, Min Zhang

Deep neural models (e. g. Transformer) naturally learn spurious features, which create a ``shortcut'' between the labels and inputs, thus impairing the generalization and robustness.

Machine Reading Comprehension Named Entity Recognition (NER) +4

Towards Representation Alignment and Uniformity in Collaborative Filtering

2 code implementations26 Jun 2022 Chenyang Wang, Yuanqing Yu, Weizhi Ma, Min Zhang, Chong Chen, Yiqun Liu, Shaoping Ma

Then, we empirically analyze the learning dynamics of typical CF methods in terms of quantified alignment and uniformity, which shows that better alignment or uniformity both contribute to higher recommendation performance.

Collaborative Filtering Recommendation Systems

Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation

1 code implementation14 Jul 2022 Min Zhang, Siteng Huang, Wenbin Li, Donglin Wang

To solve this problem, we present a plug-in Hierarchical Tree Structure-aware (HTS) method, which not only learns the relationship of FSL and pretext tasks, but more importantly, can adaptively select and aggregate feature representations generated by pretext tasks to maximize the performance of FSL tasks.

Few-Shot Image Classification Few-Shot Learning

Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network

1 code implementation24 Jul 2022 Min Zhang, Zhihong Pan, Xin Zhou, C. -C. Jay Kuo

Normalizing flow models have been used successfully for generative image super-resolution (SR) by approximating complex distribution of natural images to simple tractable distribution in latent space through Invertible Neural Networks (INN).

Image Restoration Image Super-Resolution

Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval

1 code implementation11 Aug 2022 Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao, Xiaohui Xie, Min Zhang, Shaoping Ma

By making the REM and DAMs disentangled, DDR enables a flexible training paradigm in which REM is trained with supervision once and DAMs are trained with unsupervised data.

Ad-Hoc Information Retrieval Domain Adaptation +1

Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System

1 code implementation17 Aug 2022 Ziyi Ye, Xiaohui Xie, Yiqun Liu, Zhihong Wang, Xuesong Chen, Min Zhang, Shaoping Ma

We explore the effectiveness of BTA for satisfaction modeling in two popular information access scenarios, i. e., search and recommendation.

EEG Electroencephalogram (EEG) +2

Provably Tightest Linear Approximation for Robustness Verification of Sigmoid-like Neural Networks

no code implementations21 Aug 2022 Zhaodi Zhang, Yiting Wu, Si Liu, Jing Liu, Min Zhang

Considerable efforts have been devoted to finding the so-called tighter approximations to obtain more precise verification results.

SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset

no code implementations26 Aug 2022 Saihao Huang, Lijie Wang, Zhenghua Li, Zeyang Liu, Chenhui Dou, Fukang Yan, Xinyan Xiao, Hua Wu, Min Zhang

As the first session-level Chinese dataset, CHASE contains two separate parts, i. e., 2, 003 sessions manually constructed from scratch (CHASE-C), and 3, 456 sessions translated from English SParC (CHASE-T).

SQL Parsing Text-To-SQL

Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes

no code implementations16 Sep 2022 Min Zhang, Hongyao Tang, Jianye Hao, Yan Zheng

First, we propose a unified policy abstraction theory, containing three types of policy abstraction associated to policy features at different levels.

Decision Making Metric Learning +2

SelfMix: Robust Learning Against Textual Label Noise with Self-Mixup Training

1 code implementation COLING 2022 Dan Qiao, Chenchen Dai, Yuyang Ding, Juntao Li, Qiang Chen, Wenliang Chen, Min Zhang

The conventional success of textual classification relies on annotated data, and the new paradigm of pre-trained language models (PLMs) still requires a few labeled data for downstream tasks.

text-classification Text Classification

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