Search Results for author: Zhoujun Li

Found 82 papers, 28 papers with code

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

Unleashing Potential of Evidence in Knowledge-Intensive Dialogue Generation

no code implementations15 Sep 2023 Xianjie Wu, Jian Yang, Tongliang Li, Di Liang, Shiwei Zhang, Yiyang Du, Zhoujun Li

To fully Unleash the potential of evidence, we propose a framework to effectively incorporate Evidence in knowledge-Intensive Dialogue Generation (u-EIDG).

Dialogue Generation

mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learning

no code implementations17 Aug 2023 Ying Mo, Jian Yang, Jiahao Liu, Qifan Wang, Ruoyu Chen, Jingang Wang, Zhoujun Li

A multi-view contrastive learning framework is introduced to encompass semantic contrasts between source, codeswitched, and target sentences, as well as contrasts among token-to-token relations.

Contrastive Learning named-entity-recognition +2

KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation

1 code implementation27 Jun 2023 Jiaqi Bai, Zhao Yan, Jian Yang, Xinnian Liang, Hongcheng Guo, Zhoujun Li

We propose Knowledgeable Prefix Tuning (KnowPrefix-Tuning), a two-stage tuning framework, bypassing the retrieval process in a knowledge-grounded conversation system by injecting prior knowledge into the lightweight knowledge prefix.

Dialogue Generation Response Generation +1

GripRank: Bridging the Gap between Retrieval and Generation via the Generative Knowledge Improved Passage Ranking

no code implementations29 May 2023 Jiaqi Bai, Hongcheng Guo, Jiaheng Liu, Jian Yang, Xinnian Liang, Zhao Yan, Zhoujun Li

However, the retrieved passages are not ideal for guiding answer generation because of the discrepancy between retrieval and generation, i. e., the candidate passages are all treated equally during the retrieval procedure without considering their potential to generate a proper answer.

Answer Generation Dialogue Generation +6

Unleashing Infinite-Length Input Capacity for Large-scale Language Models with Self-Controlled Memory System

1 code implementation26 Apr 2023 Xinnian Liang, Bing Wang, Hui Huang, Shuangzhi Wu, Peihao Wu, Lu Lu, Zejun Ma, Zhoujun Li

To address this limitation, we propose the Self-Controlled Memory (SCM) system to unleash infinite-length input capacity for large-scale language models.

Document Summarization Language Modelling

API-Bank: A Benchmark for Tool-Augmented LLMs

no code implementations14 Apr 2023 Minghao Li, Feifan Song, Bowen Yu, Haiyang Yu, Zhoujun Li, Fei Huang, Yongbin Li

API-Bank includes 53 commonly used API tools, a complete Tool-Augmented LLM workflow, and 264 annotated dialogues that encompass a total of 568 API calls.

Language Modelling

Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models

1 code implementation20 Mar 2023 Xinnian Liang, Zefan Zhou, Hui Huang, Shuangzhi Wu, Tong Xiao, Muyun Yang, Zhoujun Li, Chao Bian

We conduct extensive experiments on various Chinese NLP tasks to evaluate existing PLMs as well as the proposed MigBERT.

Enhancing Dialogue Summarization with Topic-Aware Global- and Local- Level Centrality

1 code implementation29 Jan 2023 Xinnian Liang, Shuangzhi Wu, Chenhao Cui, Jiaqi Bai, Chao Bian, Zhoujun Li

The global one aims to identify vital sub-topics in the dialogue and the local one aims to select the most important context in each sub-topic.

Multilingual Entity and Relation Extraction from Unified to Language-specific Training

no code implementations11 Jan 2023 Zixiang Wang, Jian Yang, Tongliang Li, Jiaheng Liu, Ying Mo, Jiaqi Bai, Longtao He, Zhoujun Li

In this paper, we propose a two-stage multilingual training method and a joint model called Multilingual Entity and Relation Extraction framework (mERE) to mitigate language interference across languages.

Relation Extraction

GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator

1 code implementation20 Dec 2022 Jian Yang, Shuming Ma, Li Dong, Shaohan Huang, Haoyang Huang, Yuwei Yin, Dongdong Zhang, Liqun Yang, Furu Wei, Zhoujun Li

Inspired by the idea of Generative Adversarial Networks (GANs), we propose a GAN-style model for encoder-decoder pre-training by introducing an auxiliary discriminator, unifying the ability of language understanding and generation in a single model.

Denoising Text Generation

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.


Know What I don't Know: Handling Ambiguous and Unanswerable Questions for Text-to-SQL

no code implementations17 Dec 2022 Bing Wang, Yan Gao, Zhoujun Li, Jian-Guang Lou

Following this study, we propose a simple yet effective counterfactual example generation approach that automatically produces ambiguous and unanswerable text-to-SQL examples.


PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models

no code implementations22 Oct 2022 Yupeng Zhang, Hongzhi Zhang, Sirui Wang, Wei Wu, Zhoujun Li

A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs).

LVP-M3: Language-aware Visual Prompt for Multilingual Multimodal Machine Translation

no code implementations19 Oct 2022 Hongcheng Guo, Jiaheng Liu, Haoyang Huang, Jian Yang, Zhoujun Li, Dongdong Zhang, Zheng Cui, Furu Wei

To this end, we first propose the Multilingual MMT task by establishing two new Multilingual MMT benchmark datasets covering seven languages.

Multimodal Machine Translation Translation

Modeling Paragraph-Level Vision-Language Semantic Alignment for Multi-Modal Summarization

no code implementations24 Aug 2022 Chenhao Cui, Xinnian Liang, Shuangzhi Wu, Zhoujun Li

The core of ViL-Sum is a joint multi-modal encoder with two well-designed tasks, image reordering and image selection.

LogLG: Weakly Supervised Log Anomaly Detection via Log-Event Graph Construction

no code implementations23 Aug 2022 Hongcheng Guo, Yuhui Guo, Renjie Chen, Jian Yang, Jiaheng Liu, Zhoujun Li, Tieqiao Zheng, Weichao Hou, Liangfan Zheng, Bo Zhang

Experiments on five benchmarks validate the effectiveness of LogLG for detecting anomalies on unlabeled log data and demonstrate that LogLG, as the state-of-the-art weakly supervised method, achieves significant performance improvements compared to existing methods.

Anomaly Detection graph construction +1

An Efficient Coarse-to-Fine Facet-Aware Unsupervised Summarization Framework based on Semantic Blocks

1 code implementation COLING 2022 Xinnian Liang, Jing Li, Shuangzhi Wu, Jiali Zeng, Yufan Jiang, Mu Li, Zhoujun Li

To tackle this problem, in this paper, we proposed an efficient Coarse-to-Fine Facet-Aware Ranking (C2F-FAR) framework for unsupervised long document summarization, which is based on the semantic block.

Document Summarization

GTrans: Grouping and Fusing Transformer Layers for Neural Machine Translation

1 code implementation29 Jul 2022 Jian Yang, Yuwei Yin, Liqun Yang, Shuming Ma, Haoyang Huang, Dongdong Zhang, Furu Wei, Zhoujun Li

Transformer structure, stacked by a sequence of encoder and decoder network layers, achieves significant development in neural machine translation.

Machine Translation Translation

HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation

1 code implementation11 Jul 2022 Jian Yang, Yuwei Yin, Shuming Ma, Dongdong Zhang, Zhoujun Li, Furu Wei

Nonetheless, multilingual training is plagued by language interference degeneration in shared parameters because of the negative interference among different translation directions, especially on high-resource languages.

Machine Translation Translation

Modeling Multi-Granularity Hierarchical Features for Relation Extraction

1 code implementation NAACL 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

TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization

no code implementations Findings (NAACL) 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.

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

PAEG: Phrase-level Adversarial Example Generation for Neural Machine Translation

no code implementations COLING 2022 Juncheng Wan, Jian Yang, Shuming Ma, Dongdong Zhang, Weinan Zhang, Yong Yu, Zhoujun Li

While end-to-end neural machine translation (NMT) has achieved impressive progress, noisy input usually leads models to become fragile and unstable.

Machine Translation NMT +1

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

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 +4

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.

Formality Style Transfer Machine Translation +2

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 NMT +1

DocBank: A Benchmark Dataset for Document Layout Analysis

2 code implementations 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

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.

Formality Style Transfer 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.

General Classification Graph Classification +2

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 +1

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.

Classification General Classification +2

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.

Table Retrieval

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 Retrieval

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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