203 citations · 650 across the 30 of their papers we have counts for
12 papers · 1 filter
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation
Jingjie Yi, Deqing Yang, Siyu Yuan +3
Emotion recognition in conversation (ERC) aims to detect the emotion for each utterance in a given conversation. The newly proposed ERC models have leveraged pre-trained language m…
Relation Aware Semi-autoregressive Semantic Parsing for NL2SQL
Junyang Huang, Yongbo Wang, Yongliang Wang +2
Natural language to SQL (NL2SQL) aims to parse a natural language with a given database into a SQL query, which widely appears in practical Internet applications. Jointly encode da…
Revisiting the Negative Data of Distantly Supervised Relation Extraction
Chenhao Xie, Jiaqing Liang, Jingping Liu +3
Distantly supervision automatically generates plenty of training samples for relation extraction. However, it also incurs two major problems: noisy labels and imbalanced training d…
A Question-answering Based Framework for Relation Extraction Validation
Jiayang Cheng, Haiyun Jiang, Deqing Yang +1
Relation extraction is an important task in knowledge acquisition and text understanding. Existing works mainly focus on improving relation extraction by extracting effective featu…
InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction
Zhendong Chu, Haiyun Jiang, Yanghua Xiao +1
Distant supervision makes it possible to automatically label bags of sentences for relation extraction by leveraging knowledge bases, but suffers from the sparse and noisy bag issu…
Complex Relation Extraction: Challenges and Opportunities
Haiyun Jiang, Qiaoben Bao, Qiao Cheng +3
Relation extraction aims to identify the target relations of entities in texts. Relation extraction is very important for knowledge base construction and text understanding. Tradit…
Knowledge-guided Open Attribute Value Extraction with Reinforcement Learning
Ye Liu, Sheng Zhang, Rui Song +2
Open attribute value extraction for emerging entities is an important but challenging task. A lot of previous works formulate the problem as a \textit{question-answering} (QA) task…
Ensuring Readability and Data-fidelity using Head-modifier Templates in Deep Type Description Generation
Jiangjie Chen, Ao Wang, Haiyun Jiang +3
A type description is a succinct noun compound which helps human and machines to quickly grasp the informative and distinctive information of an entity. Entities in most knowledge…
KBQA: Learning Question Answering over QA Corpora and Knowledge Bases
Wanyun Cui, Yanghua Xiao, Haixun Wang +3
Question answering (QA) has become a popular way for humans to access billion-scale knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and concise resu…
CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
Jindong Chen, Ao Wang, Jiangjie Chen +5
Taxonomies play an important role in machine intelligence. However, most well-known taxonomies are in English, and non-English taxonomies, especially Chinese ones, are still very r…
Deep Short Text Classification with Knowledge Powered Attention
Jindong Chen, Yizhou Hu, Jingping Liu +2
Short text classification is one of important tasks in Natural Language Processing (NLP). Unlike paragraphs or documents, short texts are more ambiguous since they have not enough…
Verb Pattern: A Probabilistic Semantic Representation on Verbs
Wanyun Cui, Xiyou Zhou, Hangyu Lin +4
Verbs are important in semantic understanding of natural language. Traditional verb representations, such as FrameNet, PropBank, VerbNet, focus on verbs' roles. These roles are too…