Chinese Computational Linguistics

Fundamental Theory and Methods of Computational Linguistics.- A Joint Model for Graph-based Chinese Dependency Parsing.- Semantic-aware Chinese Zero Pronoun Resolution with Pre-trained Semantic Dependency Parser.- Improving Sentence Classification by Multilingual Data Augmentation and Consensus Learning.- Information Retrieval, Dialogue and Question Answering.- Attention-Based Graph Neural Network with Global Context Awareness for Document Understanding.- Combining Impression Feature Representation for Multi-turn Conversational Question Answering.- Text Generation and Summarization.- Chinese Long and Short Form Choice Exploiting Neural Network Language Modeling Approaches.- Refining Data for Text Generation.- Plan-CVAE: A Planning-based Conditional Variational Autoencoder for Story Generation.- Knowledge Graph and Information Extraction.- Towards Causal Explanation Detection with Pyramid Salient-Aware Network.- Named Entity Recognition with Context-AwareDictionary Knowledge.- Chinese Named Entity Recognition via Adaptive Multi-pass Memory Network with Hierarchical Tagging Mechanism.- A Practice of Tourism Knowledge Graph Construction based on Heterogeneous Information.- A Novel Joint Framework for Multiple Chinese Events Extraction.- Entity Relative Position Representation based Multi-head Selection for Joint Entity and Relation Extraction.- Machine Translation and Multilingual Information Processing.- A Mixed Learning Objective for Neural Machine Translation.- Multi-Reward based Reinforcement Learning for Neural Machine Translation.- Minority Language Information Processing.- Low-Resource Text Classification via Cross-lingual Language Model Fine-tuning.- Constructing Uyghur Name Entity Recognition System using Neural Machine Translation Tag Projection.- Recognition Method of Important Words in Korean Text based on Reinforcement Learning.- Mongolian Questions Classification Based on Multi-Head Attention.-