Search Results for author: Pengcheng Yang

Found 29 papers, 13 papers with code

Rethinking Denoised Auto-Encoding in Language Pre-Training

no code implementations EMNLP 2021 Fuli Luo, Pengcheng Yang, Shicheng Li, Xuancheng Ren, Xu sun, Songfang Huang, Fei Huang

Pre-trained self-supervised models such as BERT have achieved striking success in learning sequence representations, especially for natural language processing.

Natural Language Understanding

Group-based Interleaved Pipeline Parallelism for Large-scale DNN Training

1 code implementation ICLR 2022 Pengcheng Yang, XiaoMing Zhang, Wenpeng Zhang, Ming Yang, Hong Wei

The recent trend of using large-scale deep neural networks (DNN) to boost performance has propelled the development of the parallel pipelining technique for efficient DNN training, which has resulted in the development of several prominent pipelines such as GPipe, PipeDream, and PipeDream-2BW.

Context-Interactive Pre-Training for Document Machine Translation

no code implementations NAACL 2021 Pengcheng Yang, Pei Zhang, Boxing Chen, Jun Xie, Weihua Luo

Document machine translation aims to translate the source sentence into the target language in the presence of additional contextual information.

Machine Translation Translation

CAPT: Contrastive Pre-Training for Learning Denoised Sequence Representations

no code implementations13 Oct 2020 Fuli Luo, Pengcheng Yang, Shicheng Li, Xuancheng Ren, Xu sun

Pre-trained self-supervised models such as BERT have achieved striking success in learning sequence representations, especially for natural language processing.

Natural Language Understanding

Visual Agreement Regularized Training for Multi-Modal Machine Translation

no code implementations27 Dec 2019 Pengcheng Yang, Boxing Chen, Pei Zhang, Xu sun

Further analysis demonstrates that the proposed regularized training can effectively improve the agreement of attention on the image, leading to better use of visual information.

Machine Translation Translation

Specificity-Driven Cascading Approach for Unsupervised Sentiment Modification

no code implementations IJCNLP 2019 Pengcheng Yang, Junyang Lin, Jingjing Xu, Jun Xie, Qi Su, Xu sun

The task of unsupervised sentiment modification aims to reverse the sentiment polarity of the input text while preserving its semantic content without any parallel data.


Pun-GAN: Generative Adversarial Network for Pun Generation

1 code implementation IJCNLP 2019 Fuli Luo, Shunyao Li, Pengcheng Yang, Lei LI, Baobao Chang, Zhifang Sui, Xu sun

It consists of a generator to produce pun sentences, and a discriminator to distinguish between the generated pun sentences and the real sentences with specific word senses.

Automatic Generation of Personalized Comment Based on User Profile

1 code implementation ACL 2019 Wenhuan Zeng, Abulikemu Abuduweili, Lei LI, Pengcheng Yang

Comments on social media are very diverse, in terms of content, style and vocabulary, which make generating comments much more challenging than other existing natural language generation~(NLG) tasks.

Comment Generation Text Generation

A Deep Reinforced Sequence-to-Set Model for Multi-Label Classification

1 code implementation ACL 2019 Pengcheng Yang, Fuli Luo, Shuming Ma, Junyang Lin, Xu sun

In this way, we can reduce the dependence of the model on the label order, as well as capture high-order correlations between labels.

General Classification Multi-Label Classification

Towards Comprehensive Description Generation from Factual Attribute-value Tables

no code implementations ACL 2019 Tianyu Liu, Fuli Luo, Pengcheng Yang, Wei Wu, Baobao Chang, Zhifang Sui

To relieve these problems, we first propose force attention (FA) method to encourage the generator to pay more attention to the uncovered attributes to avoid potential key attributes missing.

Cross-Modal Commentator: Automatic Machine Commenting Based on Cross-Modal Information

1 code implementation ACL 2019 Pengcheng Yang, Zhihan Zhang, Fuli Luo, Lei LI, Chengyang Huang, Xu sun

Automatic commenting of online articles can provide additional opinions and facts to the reader, which improves user experience and engagement on social media platforms.

Comment Generation

Enhancing Topic-to-Essay Generation with External Commonsense Knowledge

no code implementations ACL 2019 Pengcheng Yang, Lei LI, Fuli Luo, Tianyu Liu, Xu sun

Experiments show that with external commonsense knowledge and adversarial training, the generated essays are more novel, diverse, and topic-consistent than existing methods in terms of both automatic and human evaluation.

Concept-To-Text Generation

MAAM: A Morphology-Aware Alignment Model for Unsupervised Bilingual Lexicon Induction

no code implementations ACL 2019 Pengcheng Yang, Fuli Luo, Peng Chen, Tianyu Liu, Xu sun

The task of unsupervised bilingual lexicon induction (UBLI) aims to induce word translations from monolingual corpora in two languages.

Bilingual Lexicon Induction Denoising +2

Learning to Control the Fine-grained Sentiment for Story Ending Generation

no code implementations ACL 2019 Fuli Luo, Damai Dai, Pengcheng Yang, Tianyu Liu, Baobao Chang, Zhifang Sui, Xu sun

Therefore, we propose a generic and novel framework which consists of a sentiment analyzer and a sentimental generator, respectively addressing the two challenges.

Text Generation

Memorized Sparse Backpropagation

no code implementations24 May 2019 Zhiyuan Zhang, Pengcheng Yang, Xuancheng Ren, Qi Su, Xu sun

Neural network learning is usually time-consuming since backpropagation needs to compute full gradients and backpropagate them across multiple layers.

A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer

2 code implementations24 May 2019 Fuli Luo, Peng Li, Jie zhou, Pengcheng Yang, Baobao Chang, Zhifang Sui, Xu sun

Therefore, in this paper, we propose a dual reinforcement learning framework to directly transfer the style of the text via a one-step mapping model, without any separation of content and style.

reinforcement-learning Reinforcement Learning (RL) +2

Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy

no code implementations1 Nov 2018 Pengcheng Yang, Fuli Luo, Shuangzhi Wu, Jingjing Xu, Dong-dong Zhang, Xu sun

In order to avoid such sophisticated alternate optimization, we propose to learn unsupervised word mapping by directly maximizing the mean discrepancy between the distribution of transferred embedding and target embedding.

Cross-Lingual Word Embeddings Density Estimation +4

Learning Sentiment Memories for Sentiment Modification without Parallel Data

1 code implementation EMNLP 2018 Yi Zhang, Jingjing Xu, Pengcheng Yang, Xu sun

The task of sentiment modification requires reversing the sentiment of the input and preserving the sentiment-independent content.

Text Style Transfer

Identifying High-Quality Chinese News Comments Based on Multi-Target Text Matching Model

no code implementations22 Aug 2018 Deli Chen, Shuming Ma, Pengcheng Yang, Xu sun

In this work, we introduce a novel task: high-quality comment identification (HQCI), which aims to automatically assess the quality of online comments.

Informativeness Text Matching

SGM: Sequence Generation Model for Multi-label Classification

1 code implementation COLING 2018 Pengcheng Yang, Xu sun, Wei Li, Shuming Ma, Wei Wu, Houfeng Wang

Further analysis of experimental results demonstrates that the proposed methods not only capture the correlations between labels, but also select the most informative words automatically when predicting different labels.

Classification General Classification +1

Automatic Academic Paper Rating Based on Modularized Hierarchical Convolutional Neural Network

1 code implementation ACL 2018 Pengcheng Yang, Xu sun, Wei Li, Shuming Ma

As more and more academic papers are being submitted to conferences and journals, evaluating all these papers by professionals is time-consuming and can cause inequality due to the personal factors of the reviewers.

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