416 citations · 913 across the 63 of their papers we have counts for
13 papers · 1 filter
When to Talk: Chatbot Controls the Timing of Talking during Multi-turn Open-domain Dialogue Generation
Tian Lan, Xianling Mao, Heyan Huang +1
Despite the multi-turn open-domain dialogue systems have attracted more and more attention and made great progress, the existing dialogue systems are still very boring. Nearly all…
Tag Recommendation by Word-Level Tag Sequence Modeling
Xuewen Shi, Heyan Huang, Shuyang Zhao +2
In this paper, we transform tag recommendation into a word-based text generation problem and introduce a sequence-to-sequence model. The model inherits the advantages of LSTM-based…
Neural Chinese Word Segmentation as Sequence to Sequence Translation
Xuewen Shi, Heyan Huang, Ping Jian +3
Recently, Chinese word segmentation (CWS) methods using neural networks have made impressive progress. Most of them regard the CWS as a sequence labeling problem which construct mo…
Can Monolingual Pretrained Models Help Cross-Lingual Classification?
Zewen Chi, Li Dong, Furu Wei +2
Multilingual pretrained language models (such as multilingual BERT) have achieved impressive results for cross-lingual transfer. However, due to the constant model capacity, multil…
SEPT: Improving Scientific Named Entity Recognition with Span Representation
Tan Yan, Heyan Huang, Xian-Ling Mao
We introduce a new scientific named entity recognizer called SEPT, which stands for Span Extractor with Pre-trained Transformers. In recent papers, span extractors have been demons…
Generative Dialog Policy for Task-oriented Dialog Systems
Tian Lan, Xianling Mao, Heyan Huang
There is an increasing demand for task-oriented dialogue systems which can assist users in various activities such as booking tickets and restaurant reservations. In order to compl…
Cross-Lingual Natural Language Generation via Pre-Training
Zewen Chi, Li Dong, Furu Wei +3
In this work we focus on transferring supervision signals of natural language generation (NLG) tasks between multiple languages. We propose to pretrain the encoder and the decoder…
Complicated Table Structure Recognition
Zewen Chi, Heyan Huang, Heng-Da Xu +3
The task of table structure recognition aims to recognize the internal structure of a table, which is a key step to make machines understand tables. Currently, there are lots of st…
Deep Hashing for Signed Social Network Embedding
Jia-Nan Guo, Xian-Ling Mao, Xiao-Jian Jiang +3
Network embedding is a promising way of network representation, facilitating many signed social network processing and analysis tasks such as link prediction and node classificatio…
Multi-task Learning for Low-resource Second Language Acquisition Modeling
Yong Hu, Heyan Huang, Tian Lan +5
Second language acquisition (SLA) modeling is to predict whether second language learners could correctly answer the questions according to what they have learned. It is a fundamen…
Deep Cross-Modal Hashing with Hashing Functions and Unified Hash Codes Jointly Learning
Rong-Cheng Tu, Xian-Ling Mao, Bing Ma +4
Due to their high retrieval efficiency and low storage cost, cross-modal hashing methods have attracted considerable attention. Generally, compared with shallow cross-modal hashing…
Open Domain Event Extraction Using Neural Latent Variable Models
Xiao Liu, Heyan Huang, Yue Zhang
We consider open domain event extraction, the task of extracting unconstraint types of events from news clusters. A novel latent variable neural model is constructed, which is scal…
Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis
Bowen Xing, Lejian Liao, Dandan Song +4
Aspect-based sentiment analysis (ABSA) aims to predict fine-grained sentiments of comments with respect to given aspect terms or categories. In previous ABSA methods, the importanc…