Search Results for author: Lei Cui

Found 31 papers, 11 papers with code

Document AI: Benchmarks, Models and Applications

no code implementations16 Nov 2021 Lei Cui, Yiheng Xu, Tengchao Lv, Furu Wei

Document AI, or Document Intelligence, is a relatively new research topic that refers to the techniques for automatically reading, understanding, and analyzing business documents.

Document Image Classification Document Layout Analysis +2

MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding

1 code implementation16 Oct 2021 Junlong Li, Yiheng Xu, Lei Cui, Furu Wei

Multimodal pre-training with text, layout, and image has made significant progress for Visually-rich Document Understanding (VrDU), especially the fixed-layout documents such as scanned document images.

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.

Language Modelling Optical Character Recognition +1

Glancing at the Patch: Anomaly Localization With Global and Local Feature Comparison

no code implementations CVPR 2021 Shenzhi Wang, Liwei Wu, Lei Cui, Yujun Shen

More concretely, we employ a Local-Net and Global-Net to extract features from any individual patch and its surrounding respectively.

Anomaly Detection

LayoutXLM: Multimodal Pre-training for Multilingual Visually-rich Document Understanding

1 code implementation18 Apr 2021 Yiheng Xu, Tengchao Lv, Lei Cui, Guoxin Wang, Yijuan Lu, Dinei Florencio, Cha Zhang, Furu Wei

In this paper, we present LayoutXLM, a multimodal pre-trained model for multilingual document understanding, which aims to bridge the language barriers for visually-rich document understanding.

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

1 code implementation 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 +2

Unsupervised Fine-tuning for Text Clustering

no code implementations COLING 2020 Shaohan Huang, Furu Wei, Lei Cui, Xingxing Zhang, Ming Zhou

Fine-tuning with pre-trained language models (e. g. BERT) has achieved great success in many language understanding tasks in supervised settings (e. g. text classification).

Fine-tuning Language understanding +2

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

Multimodal Matching Transformer for Live Commenting

no code implementations7 Feb 2020 Chaoqun Duan, Lei Cui, Shuming Ma, Furu Wei, Conghui Zhu, Tiejun Zhao

In this work, we aim to improve the relevance between live comments and videos by modeling the cross-modal interactions among different modalities.

Text Generation

LayoutLM: Pre-training of Text and Layout for Document Image Understanding

10 code implementations31 Dec 2019 Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou

In this paper, we propose the \textbf{LayoutLM} to jointly model interactions between text and layout information across scanned document images, which is beneficial for a great number of real-world document image understanding tasks such as information extraction from scanned documents.

Document Image Classification Document Layout Analysis +1

Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification

no code implementations17 Dec 2019 Renchun You, Zhiyao Guo, Lei Cui, Xiang Long, Yingze Bao, Shilei Wen

In order to overcome these challenges, we propose to use cross-modality attention with semantic graph embedding for multi label classification.

Classification General Classification +4

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

Unsupervised Machine Commenting with Neural Variational Topic Model

no code implementations13 Sep 2018 Shuming Ma, Lei Cui, Furu Wei, Xu sun

To fully exploit the unpaired data, we completely remove the need for parallel data and propose a novel unsupervised approach to train an automatic article commenting model, relying on nothing but unpaired articles and comments.

Neural Melody Composition from Lyrics

no code implementations12 Sep 2018 Hangbo Bao, Shaohan Huang, Furu Wei, Lei Cui, Yu Wu, Chuanqi Tan, Songhao Piao, Ming Zhou

In this paper, we study a novel task that learns to compose music from natural language.

Retrieval-Enhanced Adversarial Training for Neural Response Generation

no code implementations ACL 2019 Qingfu Zhu, Lei Cui, Wei-Nan Zhang, Furu Wei, Ting Liu

Dialogue systems are usually built on either generation-based or retrieval-based approaches, yet they do not benefit from the advantages of different models.

Neural Open Information Extraction

no code implementations ACL 2018 Lei Cui, Furu Wei, Ming Zhou

Conventional Open Information Extraction (Open IE) systems are usually built on hand-crafted patterns from other NLP tools such as syntactic parsing, yet they face problems of error propagation.

Open Information Extraction

Event Detection with Burst Information Networks

no code implementations COLING 2016 Tao Ge, Lei Cui, Baobao Chang, Zhifang Sui, Ming Zhou

Retrospective event detection is an important task for discovering previously unidentified events in a text stream.

Event Detection

Aligning Coordinated Text Streams through Burst Information Network Construction and Decipherment

no code implementations27 Sep 2016 Tao Ge, Qing Dou, Xiaoman Pan, Heng Ji, Lei Cui, Baobao Chang, Zhifang Sui, Ming Zhou

We introduce a novel Burst Information Network (BINet) representation that can display the most important information and illustrate the connections among bursty entities, events and keywords in the corpus.

Decipherment Translation

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