20 citations · 78 across the 19 of their papers we have counts for
19 papers
From Spelling to Grammar: A New Framework for Chinese Grammatical Error Correction
Xiuyu Wu, Yunfang Wu
Chinese Grammatical Error Correction (CGEC) aims to generate a correct sentence from an erroneous sequence, where different kinds of errors are mixed. This paper divides the CGEC t…
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained Models
Wenbiao Li, Rui Sun, Yunfang Wu
Most of the Chinese pre-trained models adopt characters as basic units for downstream tasks. However, these models ignore the information carried by words and thus lead to the loss…
Alleviating the Knowledge-Language Inconsistency: A Study for Deep Commonsense Knowledge
Yi Zhang, Lei Li, Yunfang Wu +2
Knowledge facts are typically represented by relational triples, while we observe that some commonsense facts are represented by the triples whose forms are inconsistent with the e…
EQG-RACE: Examination-Type Question Generation
Xin Jia, Wenjie Zhou, Xu Sun +1
Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating the reading practic…
Knowledge-Aware Procedural Text Understanding with Multi-Stage Training
Zhihan Zhang, Xiubo Geng, Tao Qin +2
Procedural text describes dynamic state changes during a step-by-step natural process (e.g., photosynthesis). In this work, we focus on the task of procedural text understanding, w…
A Question Type Driven and Copy Loss Enhanced Frameworkfor Answer-Agnostic Neural Question Generation
Xiuyu Wu, Nan Jiang, Yunfang Wu
The answer-agnostic question generation is a significant and challenging task, which aims to automatically generate questions for a given sentence but without an answer. In this pa…
Jointly Modeling Aspect and Sentiment with Dynamic Heterogeneous Graph Neural Networks
Shu Liu, Wei Li, Yunfang Wu +2
Target-Based Sentiment Analysis aims to detect the opinion aspects (aspect extraction) and the sentiment polarities (sentiment detection) towards them. Both the previous pipeline a…
Query-Variant Advertisement Text Generation with Association Knowledge
Siyu Duan, Wei Li, Cai Jing +3
Online advertising is an important revenue source for many IT companies. In the search advertising scenario, advertisement text that meets the need of the search query would be mor…
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension
Xiaorui Zhou, Senlin Luo, Yunfang Wu
In reading comprehension, generating sentence-level distractors is a significant task, which requires a deep understanding of the article and question. The traditional entity-cente…
Multi-level Gated Recurrent Neural Network for Dialog Act Classification
Wei Li, Yunfang Wu
In this paper we focus on the problem of dialog act (DA) labelling. This problem has recently attracted a lot of attention as it is an important sub-part of an automatic question a…
Question-type Driven Question Generation
Wenjie Zhou, Minghua Zhang, Yunfang Wu
Question generation is a challenging task which aims to ask a question based on an answer and relevant context. The existing works suffer from the mismatching between question type…
Multi-Task Learning with Language Modeling for Question Generation
Wenjie Zhou, Minghua Zhang, Yunfang Wu
This paper explores the task of answer-aware questions generation. Based on the attention-based pointer generator model, we propose to incorporate an auxiliary task of language mod…
Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model
Wei Li, Jingjing Xu, Yancheng He +3
Automatic article commenting is helpful in encouraging user engagement and interaction on online news platforms. However, the news documents are usually too long for traditional en…
A Simple Dual-decoder Model for Generating Response with Sentiment
Xiuyu Wu, Yunfang Wu
How to generate human like response is one of the most challenging tasks for artificial intelligence. In a real application, after reading the same post different people might writ…
Learning Universal Sentence Representations with Mean-Max Attention Autoencoder
Minghua Zhang, Yunfang Wu, Weikang Li +1
In order to learn universal sentence representations, previous methods focus on complex recurrent neural networks or supervised learning. In this paper, we propose a mean-max atten…
Sememe Prediction: Learning Semantic Knowledge from Unstructured Textual Wiki Descriptions
Wei Li, Xuancheng Ren, Damai Dai +3
Huge numbers of new words emerge every day, leading to a great need for representing them with semantic meaning that is understandable to NLP systems. Sememes are defined as the mi…
An Unsupervised Model with Attention Autoencoders for Question Retrieval
Minghua Zhang, Yunfang Wu
Question retrieval is a crucial subtask for community question answering. Previous research focus on supervised models which depend heavily on training data and manual feature engi…
Improving Word Vector with Prior Knowledge in Semantic Dictionary
Wei Li, Yunfang Wu, Xueqiang Lv
Using low dimensional vector space to represent words has been very effective in many NLP tasks. However, it doesn't work well when faced with the problem of rare and unseen words.…
Hierarchical Gated Recurrent Neural Tensor Network for Answer Triggering
Wei Li, Yunfang Wu
In this paper, we focus on the problem of answer triggering ad-dressed by Yang et al. (2015), which is a critical component for a real-world question answering system. We employ a…