Search Results for author: Wei Lu

Found 98 papers, 46 papers with code

SmartCiteCon: Implicit Citation Context Extraction from Academic Literature Using Supervised Learning

no code implementations WOSP 2020 Chenrui Guo, Haoran Cui, Li Zhang, Jiamin Wang, Wei Lu, Jian Wu

The tool is built on a Support Vector Machine (SVM) model trained on a set of 7, 058 manually annotated citation context sentences, curated from 34, 000 papers from the ACL Anthology.

Re-examining the Role of Schema Linking in Text-to-SQL

no code implementations EMNLP 2020 Wenqiang Lei, Weixin Wang, Zhixin Ma, Tian Gan, Wei Lu, Min-Yen Kan, Tat-Seng Chua

By providing a schema linking corpus based on the Spider text-to-SQL dataset, we systematically study the role of schema linking.

Text-To-Sql

ADT-SSL: Adaptive Dual-Threshold for Semi-Supervised Learning

no code implementations21 May 2022 Zechen Liang, Yuan-Gen Wang, Wei Lu, Xiaochun Cao

Semi-Supervised Learning (SSL) has advanced classification tasks by inputting both labeled and unlabeled data to train a model jointly.

Implicit N-grams Induced by Recurrence

1 code implementation5 May 2022 Xiaobing Sun, Wei Lu

Although self-attention based models such as Transformers have achieved remarkable successes on natural language processing (NLP) tasks, recent studies reveal that they have limitations on modeling sequential transformations (Hahn, 2020), which may prompt re-examinations of recurrent neural networks (RNNs) that demonstrated impressive results on handling sequential data.

Language Modelling Sentiment Analysis

A Deep Learning based No-reference Quality Assessment Model for UGC Videos

1 code implementation29 Apr 2022 Wei Sun, Xiongkuo Min, Wei Lu, Guangtao Zhai

The proposed model utilizes very sparse frames to extract spatial features and dense frames (i. e. the video chunk) with a very low spatial resolution to extract motion features, which thereby has low computational complexity.

Image Quality Assessment Video Quality Assessment +2

Profiling Neural Blocks and Design Spaces for Mobile Neural Architecture Search

1 code implementation25 Sep 2021 Keith G. Mills, Fred X. Han, Jialin Zhang, SEYED SAEED CHANGIZ REZAEI, Fabian Chudak, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

Neural architecture search automates neural network design and has achieved state-of-the-art results in many deep learning applications.

Neural Architecture Search

L$^{2}$NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning

no code implementations25 Sep 2021 Keith G. Mills, Fred X. Han, Mohammad Salameh, SEYED SAEED CHANGIZ REZAEI, Linglong Kong, Wei Lu, Shuo Lian, Shangling Jui, Di Niu

In this paper, we propose L$^{2}$NAS, which learns to intelligently optimize and update architecture hyperparameters via an actor neural network based on the distribution of high-performing architectures in the search history.

Hyperparameter Optimization Neural Architecture Search +1

A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis

1 code implementation EMNLP 2021 Jiawei Liu, Kaisong Song, Yangyang Kang, Guoxiu He, Zhuoren Jiang, Changlong Sun, Wei Lu, Xiaozhong Liu

Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension.

Chatbot Multi-Task Learning

To be Closer: Learning to Link up Aspects with Opinions

1 code implementation EMNLP 2021 Yuxiang Zhou, Lejian Liao, Yang Gao, Zhanming Jie, Wei Lu

Dependency parse trees are helpful for discovering the opinion words in aspect-based sentiment analysis (ABSA).

Aspect-Based Sentiment Analysis

Exploring Task Difficulty for Few-Shot Relation Extraction

1 code implementation EMNLP 2021 Jiale Han, Bo Cheng, Wei Lu

Few-shot relation extraction (FSRE) focuses on recognizing novel relations by learning with merely a handful of annotated instances.

Contrastive Learning Meta-Learning +1

Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction

1 code implementation11 Sep 2021 Guoshun Nan, Guoqing Luo, Sicong Leng, Yao Xiao, Wei Lu

Dialogue-based relation extraction (DiaRE) aims to detect the structural information from unstructured utterances in dialogues.

Dialog Relation Extraction

No-Reference Quality Assessment for 3D Colored Point Cloud and Mesh Models

2 code implementations5 Jul 2021 ZiCheng Zhang, Wei Sun, Xiongkuo Min, Tao Wang, Wei Lu, Guangtao Zhai

Therefore, many related studies such as point cloud quality assessment (PCQA) and mesh quality assessment (MQA) have been carried out to measure the visual quality degradations of 3D models.

Point Cloud Quality Assessment

Mixed Cross Entropy Loss for Neural Machine Translation

1 code implementation30 Jun 2021 Haoran Li, Wei Lu

In neural machine translation, cross entropy (CE) is the standard loss function in two training methods of auto-regressive models, i. e., teacher forcing and scheduled sampling.

Machine Translation Translation

Detection of Deepfake Videos Using Long Distance Attention

no code implementations24 Jun 2021 Wei Lu, Lingyi Liu, Junwei Luo, Xianfeng Zhao, Yicong Zhou, Jiwu Huang

And a spatial-temporal model is proposed which has two components for capturing spatial and temporal forgery traces in global perspective respectively.

Face Swapping Frame

Interventional Video Grounding with Dual Contrastive Learning

1 code implementation CVPR 2021 Guoshun Nan, Rui Qiao, Yao Xiao, Jun Liu, Sicong Leng, Hao Zhang, Wei Lu

2) Meanwhile, we introduce a dual contrastive learning approach (DCL) to better align the text and video by maximizing the mutual information (MI) between query and video clips, and the MI between start/end frames of a target moment and the others within a video to learn more informative visual representations.

Causal Inference Contrastive Learning +1

Generative Adversarial Neural Architecture Search

no code implementations19 May 2021 SEYED SAEED CHANGIZ REZAEI, Fred X. Han, Di Niu, Mohammad Salameh, Keith Mills, Shuo Lian, Wei Lu, Shangling Jui

Despite the empirical success of neural architecture search (NAS) in deep learning applications, the optimality, reproducibility and cost of NAS schemes remain hard to assess.

Neural Architecture Search

A parallel-network continuous quantitative trading model with GARCH and PPO

no code implementations8 May 2021 Zhishun Wang, Wei Lu, Kaixin Zhang, TianHao Li, Zixi Zhao

It is a difficult task for both professional investors and individual traders continuously making profit in stock market.

Decision Making reinforcement-learning

Better Feature Integration for Named Entity Recognition

1 code implementation NAACL 2021 Lu Xu, Zhanming Jie, Wei Lu, Lidong Bing

We believe this is because both types of features - the contextual information captured by the linear sequences and the structured information captured by the dependency trees may complement each other.

Named Entity Recognition NER

Counterfactual Thinking for Long-tailed Information Extraction

no code implementations1 Jan 2021 Guoshun Nan, Jiaqi Zeng, Rui Qiao, Wei Lu

However, in practice, the long-tailed and imbalanced data may lead to severe bias issues for deep learning models, due to very few training instances available for the tail classes.

Causal Inference Event Detection +7

SEQUENCE-LEVEL FEATURES: HOW GRU AND LSTM CELLS CAPTURE N-GRAMS

no code implementations1 Jan 2021 Xiaobing Sun, Wei Lu

Based on the closed-form approximations of the hidden states, we argue that the effectiveness of the cells may be attributed to a type of sequence-level representations brought in by the gating mechanism, which enables the cells to encode sequence-level features along with token-level features.

Language Modelling Sentiment Analysis

Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders

2 code implementations EMNLP 2020 Jue Wang, Wei Lu

In this work, we propose the novel {\em table-sequence encoders} where two different encoders -- a table encoder and a sequence encoder are designed to help each other in the representation learning process.

Joint Entity and Relation Extraction Named Entity Recognition +2

Position-Aware Tagging for Aspect Sentiment Triplet Extraction

4 code implementations EMNLP 2020 Lu Xu, Hao Li, Wei Lu, Lidong Bing

Our observation is that the three elements within a triplet are highly related to each other, and this motivates us to build a joint model to extract such triplets using a sequence tagging approach.

Aspect Sentiment Triplet Extraction

Aspect Based Sentiment Analysis with Aspect-Specific Opinion Spans

1 code implementation EMNLP 2020 Lu Xu, Lidong Bing, Wei Lu, Fei Huang

Such a design allows the model to extract aspect-specific opinion spans and then evaluate sentiment polarity by exploiting the extracted opinion features.

Extract Aspect

RPT: Learning Point Set Representation for Siamese Visual Tracking

no code implementations8 Aug 2020 Ziang Ma, Linyuan Wang, HaiTao Zhang, Wei Lu, Jun Yin

While remarkable progress has been made in robust visual tracking, accurate target state estimation still remains a highly challenging problem.

Visual Tracking

Reasoning with Latent Structure Refinement for Document-Level Relation Extraction

1 code implementation ACL 2020 Guoshun Nan, Zhijiang Guo, Ivan Sekulić, Wei Lu

Document-level relation extraction requires integrating information within and across multiple sentences of a document and capturing complex interactions between inter-sentence entities.

Relational Reasoning Relation Extraction

WN-Salience: A Corpus of News Articles with Entity Salience Annotations

no code implementations LREC 2020 Chuan Wu, Evangelos Kanoulas, Maarten de Rijke, Wei Lu

To support research on entity salience, we present a new dataset, the WikiNews Salience dataset (WN-Salience), which can be used to benchmark tasks such as entity salience detection and salient entity linking.

Entity Linking

ENT-DESC: Entity Description Generation by Exploring Knowledge Graph

1 code implementation EMNLP 2020 Liying Cheng, Dekun Wu, Lidong Bing, Yan Zhang, Zhanming Jie, Wei Lu, Luo Si

Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language description.

Graph-to-Sequence Knowledge Graphs +1

Pre-training for Abstractive Document Summarization by Reinstating Source Text

no code implementations EMNLP 2020 Yanyan Zou, Xingxing Zhang, Wei Lu, Furu Wei, Ming Zhou

The main idea is that, given an input text artificially constructed from a document, a model is pre-trained to reinstate the original document.

Abstractive Text Summarization Document Summarization

Adversarial Deep Network Embedding for Cross-network Node Classification

2 code implementations18 Feb 2020 Xiao Shen, Quanyu Dai, Fu-Lai Chung, Wei Lu, Kup-Sze Choi

This motivates us to propose an adversarial cross-network deep network embedding (ACDNE) model to integrate adversarial domain adaptation with deep network embedding so as to learn network-invariant node representations that can also well preserve the network structural information.

Classification Domain Adaptation +3

Mining Commonsense Facts from the Physical World

no code implementations8 Feb 2020 Yanyan Zou, Wei Lu, Xu sun

In this paper, we propose a new task of mining commonsense facts from the raw text that describes the physical world.

Knowledge Base Completion

Self-Directed Online Machine Learning for Topology Optimization

1 code implementation4 Feb 2020 Changyu Deng, Yizhou Wang, Can Qin, Yun Fu, Wei Lu

A small number of training data is generated dynamically based on the DNN's prediction of the optimum.

online learning Stochastic Optimization

Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model

no code implementations3 Jan 2020 Guoxiu He, Zhe Gao, Zhuoren Jiang, Yangyang Kang, Changlong Sun, Xiaozhong Liu, Wei Lu

The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language.

Reading Comprehension

Learning Explicit and Implicit Structures for Targeted Sentiment Analysis

no code implementations IJCNLP 2019 Hao Li, Wei Lu

In this work, we argue that both types of information (implicit and explicit structural information) are crucial for building a successful targeted sentiment analysis model.

Sentiment Analysis

UER: An Open-Source Toolkit for Pre-training Models

1 code implementation IJCNLP 2019 Zhe Zhao, Hui Chen, Jinbin Zhang, Xin Zhao, Tao Liu, Wei Lu, Xi Chen, Haotang Deng, Qi Ju, Xiaoyong Du

Existing works, including ELMO and BERT, have revealed the importance of pre-training for NLP tasks.

Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entities

1 code implementation IJCNLP 2019 Bailin Wang, Wei Lu

In medical documents, it is possible that an entity of interest not only contains a discontiguous sequence of words but also overlaps with another entity.

Joint Detection and Location of English Puns

1 code implementation NAACL 2019 Yanyan Zou, Wei Lu

A pun is a form of wordplay for an intended humorous or rhetorical effect, where a word suggests two or more meanings by exploiting polysemy (homographic pun) or phonological similarity to another word (heterographic pun).

Quantity Tagger: A Latent-Variable Sequence Labeling Approach to Solving Addition-Subtraction Word Problems

1 code implementation ACL 2019 Yanyan Zou, Wei Lu

An arithmetic word problem typically includes a textual description containing several constant quantities.

Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning

1 code implementation TACL 2019 Zhijiang Guo, Yan Zhang, Zhiyang Teng, Wei Lu

We focus on graph-to-sequence learning, which can be framed as transducing graph structures to sequences for text generation.

Graph-to-Sequence Machine Translation +2

Twitter Homophily: Network Based Prediction of User's Occupation

1 code implementation ACL 2019 Jiaqi Pan, Rishabh Bhardwaj, Wei Lu, Hai Leong Chieu, Xinghao Pan, Ni Yi Puay

In this paper, we investigate the importance of social network information compared to content information in the prediction of a Twitter user{'}s occupational class.

Attention Guided Graph Convolutional Networks for Relation Extraction

2 code implementations ACL 2019 Zhijiang Guo, Yan Zhang, Wei Lu

Dependency trees convey rich structural information that is proven useful for extracting relations among entities in text.

Relation Extraction

Better Modeling of Incomplete Annotations for Named Entity Recognition

no code implementations NAACL 2019 Zhanming Jie, Pengjun Xie, Wei Lu, Ruixue Ding, Linlin Li

Supervised approaches to named entity recognition (NER) are largely developed based on the assumption that the training data is fully annotated with named entity information.

Named Entity Recognition NER

Neural Chinese Address Parsing

no code implementations NAACL 2019 Hao Li, Wei Lu, Pengjun Xie, Linlin Li

This paper introduces a new task {--} Chinese address parsing {--} the task of mapping Chinese addresses into semantically meaningful chunks.

Structured Prediction

Labeling Gaps Between Words: Recognizing Overlapping Mentions with Mention Separators

1 code implementation EMNLP 2017 Aldrian Obaja Muis, Wei Lu

We present some theoretical analysis on the differences between our model and a recently proposed model for recognizing overlapping mentions, and discuss the possible implications of the differences.

Efficient Dependency-Guided Named Entity Recognition

1 code implementation19 Oct 2018 Zhanming Jie, Aldrian Obaja Muis, Wei Lu

It has been shown previously that such information can be used to improve the performance of NER (Sasano and Kurohashi 2008, Ling and Weld 2012).

Named Entity Recognition NER +1

Learning to Recognize Discontiguous Entities

1 code implementation EMNLP 2016 Aldrian Obaja Muis, Wei Lu

This paper focuses on the study of recognizing discontiguous entities.

Weak Semi-Markov CRFs for NP Chunking in Informal Text

no code implementations19 Oct 2018 Aldrian Obaja Muis, Wei Lu

This paper introduces a new annotated corpus based on an existing informal text corpus: the NUS SMS Corpus (Chen and Kan, 2013).

Chunking

Neural Adaptation Layers for Cross-domain Named Entity Recognition

1 code implementation EMNLP 2018 Bill Yuchen Lin, Wei Lu

Recent research efforts have shown that neural architectures can be effective in conventional information extraction tasks such as named entity recognition, yielding state-of-the-art results on standard newswire datasets.

Cross-Domain Named Entity Recognition Domain Adaptation +1

Neural Segmental Hypergraphs for Overlapping Mention Recognition

1 code implementation EMNLP 2018 Bailin Wang, Wei Lu

In this work, we propose a novel segmental hypergraph representation to model overlapping entity mentions that are prevalent in many practical datasets.

Nested Mention Recognition Nested Named Entity Recognition +1

Better Transition-Based AMR Parsing with a Refined Search Space

no code implementations EMNLP 2018 Zhijiang Guo, Wei Lu

This paper introduces a simple yet effective transition-based system for Abstract Meaning Representation (AMR) parsing.

AMR Parsing Named Entity Recognition +1

Dependency-based Hybrid Trees for Semantic Parsing

no code implementations EMNLP 2018 Zhanming Jie, Wei Lu

We propose a novel dependency-based hybrid tree model for semantic parsing, which converts natural language utterance into machine interpretable meaning representations.

Semantic Parsing

Reproducible and Interpretable Spiculation Quantification for Lung Cancer Screening

no code implementations24 Aug 2018 Wookjin Choi, Saad Nadeem, Sadegh Riyahi, Joseph O. Deasy, Allen Tannenbaum, Wei Lu

The spiculation quantification measures was then applied to the radiomics framework for pathological malignancy prediction with reproducible semi-automatic segmentation of nodule.

Learning with Structured Representations for Negation Scope Extraction

no code implementations ACL 2018 Hao Li, Wei Lu

We report an empirical study on the task of negation scope extraction given the negation cue.

Sentiment Analysis

Learning Cross-lingual Distributed Logical Representations for Semantic Parsing

no code implementations ACL 2018 Yanyan Zou, Wei Lu

In this work, we present a study to show how learning distributed representations of the logical forms from data annotated in different languages can be used for improving the performance of a monolingual semantic parser.

Semantic Parsing

SemEval-2018 Task 8: Semantic Extraction from CybersecUrity REports using Natural Language Processing (SecureNLP)

no code implementations SEMEVAL 2018 Ph, Peter i, Amila Silva, Wei Lu

This paper describes the SemEval 2018 shared task on semantic extraction from cybersecurity reports, which is introduced for the first time as a shared task on SemEval.

Malware Detection

Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect

1 code implementation ICLR 2018 Xiang Wei, Boqing Gong, Zixia Liu, Wei Lu, Liqiang Wang

Despite being impactful on a variety of problems and applications, the generative adversarial nets (GANs) are remarkably difficult to train.

A Unified Framework for Structured Prediction: From Theory to Practice

no code implementations EMNLP 2017 Wei Lu

Based on such a framework, we show how some seemingly complicated structured prediction models such as a semantic parsing model (Lu et al., 2008; Lu, 2014) can be implemented conveniently and quickly.

AMR Parsing Chunking +3

Digital image splicing detection based on Markov features in QDCT and QWT domain

no code implementations28 Aug 2017 Ruxin Wang, Wei Lu, Shijun Xiang, Xianfeng Zhao, Jinwei Wang

In this paper, a color image splicing detection approach is proposed based on Markov transition probability of quaternion component separation in quaternion discrete cosine transform (QDCT) domain and quaternion wavelet transform (QWT) domain.

Topical Coherence in LDA-based Models through Induced Segmentation

1 code implementation ACL 2017 Hesam Amoualian, Wei Lu, Eric Gaussier, Georgios Balikas, Massih R. Amini, Marianne Clausel

This paper presents an LDA-based model that generates topically coherent segments within documents by jointly segmenting documents and assigning topics to their words.

Ad-Hoc Information Retrieval General Classification +2

MalwareTextDB: A Database for Annotated Malware Articles

no code implementations ACL 2017 Swee Kiat Lim, Aldrian Obaja Muis, Wei Lu, Chen Hui Ong

Cybersecurity risks and malware threats are becoming increasingly dangerous and common.

Refutations on "Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study"

2 code implementations15 May 2017 Wei Lu, Xiaokui Xiao, Amit Goyal, Keke Huang, Laks V. S. Lakshmanan

In a recent SIGMOD paper titled "Debunking the Myths of Influence Maximization: An In-Depth Benchmarking Study", Arora et al. [1] undertake a performance benchmarking study of several well-known algorithms for influence maximization.

Social and Information Networks

Rhetorical relations for information retrieval

no code implementations5 Apr 2017 Christina Lioma, Birger Larsen, Wei Lu

Typically, every part in most coherent text has some plausible reason for its presence, some function that it performs to the overall semantics of the text.

Information Retrieval Language Modelling

Deep neural networks for learning graph representations

no code implementations Thirtieth AAAI Conference on Artificial Intelligence 2016 Shaosheng Cao, Wei Lu, Qiongkai Xu

Different from other previous research efforts, we adopt a random surfing model to capture graph structural information directly, instead of using the sampling-based method for generating linear sequences proposed by Perozzi et al. (2014).

Denoising Graph Clustering

From Competition to Complementarity: Comparative Influence Diffusion and Maximization

no code implementations1 Jul 2015 Wei Lu, Wei Chen, Laks. V. S. Lakshmanan

We study two natural optimization problems, Self Influence Maximization and Complementary Influence Maximization, in a novel setting with complementary entities.

Social and Information Networks Physics and Society H.2.8

Replicating Kernels with a Short Stride Allows Sparse Reconstructions with Fewer Independent Kernels

no code implementations17 Jun 2014 Peter F. Schultz, Dylan M. Paiton, Wei Lu, Garrett T. Kenyon

We find, for example, that for 16x16-pixel receptive fields, using eight kernels and a stride of 2 leads to sparse reconstructions of comparable quality as using 512 kernels and a stride of 16 (the nonoverlapping case).

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