Search Results for author: Zhoujun Li

Found 55 papers, 16 papers with code

Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation

1 code implementation ACL 2022 Xinyu Pi, Bing Wang, Yan Gao, Jiaqi Guo, Zhoujun Li, Jian-Guang Lou

The robustness of Text-to-SQL parsers against adversarial perturbations plays a crucial role in delivering highly reliable applications.

Text-To-Sql

TWT: Table with Written Text for Controlled Data-to-Text Generation

no code implementations Findings (EMNLP) 2021 Tongliang Li, Lei Fang, Jian-Guang Lou, Zhoujun Li

In this paper, we propose to generate text conditioned on the structured data (table) and a prefix (the written text) by leveraging the pre-trained models.

Data-to-Text Generation

TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization

no code implementations9 Apr 2022 Ze Yang, Liran Wang, Zhoujin Tian, Wei Wu, Zhoujun Li

Another is that applying the existing pre-trained models to this task is tricky because of the structural dependence within the conversation and its informal expression, etc.

Modeling Multi-Granularity Hierarchical Features for Relation Extraction

1 code implementation9 Apr 2022 Xinnian Liang, Shuangzhi Wu, Mu Li, Zhoujun Li

In this paper, we propose a novel method to extract multi-granularity features based solely on the original input sentences.

Relation Extraction

Neighbor Enhanced Graph Convolutional Networks for Node Classification and Recommendation

no code implementations30 Mar 2022 Hao Chen, Zhong Huang, Yue Xu, Zengde Deng, Feiran Huang, Peng He, Zhoujun Li

The experimental results verify that our proposed NEGCN framework can significantly enhance the performance for various typical GCN models on both node classification and recommendation tasks.

Classification Node Classification

TransLog: A Unified Transformer-based Framework for Log Anomaly Detection

no code implementations31 Dec 2021 Hongcheng Guo, Xingyu Lin, Jian Yang, Yi Zhuang, Jiaqi Bai, Tieqiao Zheng, Bo Zhang, Zhoujun Li

Therefore, we propose a unified Transformer-based framework for log anomaly detection (\ourmethod{}), which is comprised of the pretraining and adapter-based tuning stage.

Anomaly Detection

TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models

2 code implementations21 Sep 2021 Minghao Li, Tengchao Lv, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, Furu Wei

Existing approaches for text recognition are usually built based on CNN for image understanding and RNN for char-level text generation.

Handwritten Text Recognition Language Modelling +2

Unsupervised Keyphrase Extraction by Jointly Modeling Local and Global Context

1 code implementation EMNLP 2021 Xinnian Liang, Shuangzhi Wu, Mu Li, Zhoujun Li

In terms of the local view, we first build a graph structure based on the document where phrases are regarded as vertices and the edges are similarities between vertices.

Document Embedding Keyphrase Extraction

Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis

no code implementations5 Sep 2021 Tong Sha, Wei zhang, Tong Shen, Zhoujun Li, Tao Mei

Deep person generation has attracted extensive research attention due to its wide applications in virtual agents, video conferencing, online shopping and art/movie production.

Data Augmentation Talking Head Generation

Multilingual Agreement for Multilingual Neural Machine Translation

no code implementations ACL 2021 Jian Yang, Yuwei Yin, Shuming Ma, Haoyang Huang, Dongdong Zhang, Zhoujun Li, Furu Wei

Although multilingual neural machine translation (MNMT) enables multiple language translations, the training process is based on independent multilingual objectives.

Machine Translation Translation

Smart-Start Decoding for Neural Machine Translation

no code implementations NAACL 2021 Jian Yang, Shuming Ma, Dongdong Zhang, Juncheng Wan, Zhoujun Li, Ming Zhou

Most current neural machine translation models adopt a monotonic decoding order of either left-to-right or right-to-left.

Machine Translation Translation

Non-Recursive Graph Convolutional Networks

no code implementations9 May 2021 Hao Chen, Zengde Deng, Yue Xu, Zhoujun Li

In this way, each node can be directly represented by concatenating the information extracted independently from each hop of its neighbors thereby avoiding the recursive neighborhood expansion across layers.

Node Classification Representation Learning

Towards Overcoming False Positives in Visual Relationship Detection

no code implementations23 Dec 2020 Daisheng Jin, Xiao Ma, Chongzhi Zhang, Yizhuo Zhou, Jiashu Tao, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, Zhoujun Li, Xianglong Liu, Hongsheng Li

We observe that during training, the relationship proposal distribution is highly imbalanced: most of the negative relationship proposals are easy to identify, e. g., the inaccurate object detection, which leads to the under-fitting of low-frequency difficult proposals.

Graph Attention Human-Object Interaction Detection +2

Formality Style Transfer with Shared Latent Space

1 code implementation COLING 2020 Yunli Wang, Yu Wu, Lili Mou, Zhoujun Li, WenHan Chao

Conventional approaches for formality style transfer borrow models from neural machine translation, which typically requires massive parallel data for training.

Machine Translation Style Transfer +1

StyleDGPT: Stylized Response Generation with Pre-trained Language Models

1 code implementation Findings of the Association for Computational Linguistics 2020 Ze Yang, Wei Wu, Can Xu, Xinnian Liang, Jiaqi Bai, Liran Wang, Wei Wang, Zhoujun Li

Generating responses following a desired style has great potentials to extend applications of open-domain dialogue systems, yet is refrained by lacking of parallel data for training.

Response Generation

Improving Neural Machine Translation with Soft Template Prediction

no code implementations ACL 2020 Jian Yang, Shuming Ma, Dong-dong Zhang, Zhoujun Li, Ming Zhou

Although neural machine translation (NMT) has achieved significant progress in recent years, most previous NMT models only depend on the source text to generate translation.

Machine Translation Translation

DocBank: A Benchmark Dataset for Document Layout Analysis

1 code implementation COLING 2020 Minghao Li, Yiheng Xu, Lei Cui, Shaohan Huang, Furu Wei, Zhoujun Li, Ming Zhou

DocBank is constructed using a simple yet effective way with weak supervision from the \LaTeX{} documents available on the arXiv. com.

Document Layout Analysis

TableBank: Table Benchmark for Image-based Table Detection and Recognition

1 code implementation LREC 2020 Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, Zhoujun Li

We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.

Table Detection

Open Domain Dialogue Generation with Latent Images

no code implementations4 Apr 2020 Ze Yang, Wei Wu, Huang Hu, Can Xu, Wei Wang, Zhoujun Li

Thus, we propose learning a response generation model with both image-grounded dialogues and textual dialogues by assuming that the visual scene information at the time of a conversation can be represented by an image, and trying to recover the latent images of the textual dialogues through text-to-image generation techniques.

Dialogue Generation Response Generation +2

Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer

no code implementations IJCNLP 2019 Yunli Wang, Yu Wu, Lili Mou, Zhoujun Li, WenHan Chao

Formality text style transfer plays an important role in various NLP applications, such as non-native speaker assistants and child education.

Style Transfer Text Style Transfer

Low-Resource Response Generation with Template Prior

1 code implementation IJCNLP 2019 Ze Yang, Wei Wu, Jian Yang, Can Xu, Zhoujun Li

Since the paired data now is no longer enough to train a neural generation model, we consider leveraging the large scale of unpaired data that are much easier to obtain, and propose response generation with both paired and unpaired data.

Response Generation

Label-Aware Graph Convolutional Networks

no code implementations10 Jul 2019 Hao Chen, Yue Xu, Feiran Huang, Zengde Deng, Wenbing Huang, Senzhang Wang, Peng He, Zhoujun Li

In this paper, we consider the problem of node classification and propose the Label-Aware Graph Convolutional Network (LAGCN) framework which can directly identify valuable neighbors to enhance the performance of existing GCN models.

Classification General Classification +3

Multi-Hot Compact Network Embedding

no code implementations7 Mar 2019 Chaozhuo Li, Senzhang Wang, Philip S. Yu, Zhoujun Li

Specifically, we propose a MCNE model to learn compact embeddings from pre-learned node features.

Network Embedding

TableBank: A Benchmark Dataset for Table Detection and Recognition

2 code implementations LREC 2020 Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou, Zhoujun Li

We present TableBank, a new image-based table detection and recognition dataset built with novel weak supervision from Word and Latex documents on the internet.

Table Detection

Response Generation by Context-aware Prototype Editing

3 code implementations19 Jun 2018 Yu Wu, Furu Wei, Shaohan Huang, Yunli Wang, Zhoujun Li, Ming Zhou

Open domain response generation has achieved remarkable progress in recent years, but sometimes yields short and uninformative responses.

Informativeness Response Generation

TI-CNN: Convolutional Neural Networks for Fake News Detection

2 code implementations3 Jun 2018 Yang Yang, Lei Zheng, Jiawei Zhang, Qingcai Cui, Zhoujun Li, Philip S. Yu

By projecting the explicit and latent features into a unified feature space, TI-CNN is trained with both the text and image information simultaneously.

Fact Checking Fake News Detection

r-Instance Learning for Missing People Tweets Identification

no code implementations28 May 2018 Yang Yang, Haoyan Liu, Xia Hu, Jiawei Zhang, Xiao-Ming Zhang, Zhoujun Li, Philip S. Yu

The number of missing people (i. e., people who get lost) greatly increases in recent years.

Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots

no code implementations ACL 2018 Yu Wu, Wei Wu, Zhoujun Li, Ming Zhou

We propose a method that can leverage unlabeled data to learn a matching model for response selection in retrieval-based chatbots.

Assertion-based QA with Question-Aware Open Information Extraction

no code implementations23 Jan 2018 Zhao Yan, Duyu Tang, Nan Duan, Shujie Liu, Wendi Wang, Daxin Jiang, Ming Zhou, Zhoujun Li

We present assertion based question answering (ABQA), an open domain question answering task that takes a question and a passage as inputs, and outputs a semi-structured assertion consisting of a subject, a predicate and a list of arguments.

Learning-To-Rank Open-Domain Question Answering +2

Towards Interpretable Chit-chat: Open Domain Dialogue Generation with Dialogue Acts

no code implementations ICLR 2018 Wei Wu, Can Xu, Yu Wu, Zhoujun Li

Conventional methods model open domain dialogue generation as a black box through end-to-end learning from large scale conversation data.

Dialogue Generation Response Generation

A Sequential Matching Framework for Multi-turn Response Selection in Retrieval-based Chatbots

no code implementations CL 2019 Yu Wu, Wei Wu, Chen Xing, Can Xu, Zhoujun Li, Ming Zhou

The task requires matching a response candidate with a conversation context, whose challenges include how to recognize important parts of the context, and how to model the relationships among utterances in the context.

Learning Social Image Embedding with Deep Multimodal Attention Networks

no code implementations18 Oct 2017 Feiran Huang, Xiao-Ming Zhang, Zhoujun Li, Tao Mei, Yueying He, Zhonghua Zhao

Extensive experiments are conducted to investigate the effectiveness of our approach in the applications of multi-label classification and cross-modal search.

General Classification Link Prediction +1

Content-Based Table Retrieval for Web Queries

no code implementations8 Jun 2017 Zhao Yan, Duyu Tang, Nan Duan, Junwei Bao, Yuanhua Lv, Ming Zhou, Zhoujun Li

Understanding the connections between unstructured text and semi-structured table is an important yet neglected problem in natural language processing.

Jointly Extracting Relations with Class Ties via Effective Deep Ranking

1 code implementation ACL 2017 Hai Ye, WenHan Chao, Zhunchen Luo, Zhoujun Li

Exploiting class ties between relations of one entity tuple will be promising for distantly supervised relation extraction.

Relation Extraction

Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-based Chatbots

3 code implementations ACL 2017 Yu Wu, Wei Wu, Chen Xing, Ming Zhou, Zhoujun Li

Existing work either concatenates utterances in context or matches a response with a highly abstract context vector finally, which may lose relationships among utterances or important contextual information.

Conversational Response Selection

Knowledge Enhanced Hybrid Neural Network for Text Matching

no code implementations15 Nov 2016 Yu Wu, Wei Wu, Zhoujun Li, Ming Zhou

Long text brings a big challenge to semantic matching due to their complicated semantic and syntactic structures.

Question Answering Text Matching

Detecting Context Dependent Messages in a Conversational Environment

no code implementations COLING 2016 Chaozhuo Li, Yu Wu, Wei Wu, Chen Xing, Zhoujun Li, Ming Zhou

While automatic response generation for building chatbot systems has drawn a lot of attention recently, there is limited understanding on when we need to consider the linguistic context of an input text in the generation process.

Chatbot Response Generation

Response Selection with Topic Clues for Retrieval-based Chatbots

1 code implementation30 Apr 2016 Yu Wu, Wei Wu, Zhoujun Li, Ming Zhou

The message vector, the response vector, and the two topic vectors are fed to neural tensors to calculate a matching score.

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