Chinese Computational Linguistics

Linguistics and Cognitive Science.- Discourse Markers as the Classificatory Factors of Speech Acts.- Fundamental Theory and Methods of Computational Linguistics.- DIFM: An effective deep interaction and fusion model for sentence matching.- ConIsI: A Contrastive Framework with Inter-sentence Interaction for Self-supervised Sentence Representation.- Information Retrieval, Dialogue and Question Answering.- Data Synthesis and Iterative Refinement for Neural Semantic Parsing without Annotated Logical Forms.- EventBERT: Incorporating Event-based Semantics for Natural Language Understanding.- An Exploration of Prompt-Based Zero-Shot Relation Extraction Method.- Abstains from Prediction: Towards Robust Relation Extraction in Real World.- Using Extracted Emotion Cause to Improve Content-Relevance for Empathetic Conversation Generation.- Text Generation and Summarization.- To Adapt or to Fine-tune: A Case Study on Abstractive Summarization.- Knowledge Graph and Information Extraction.- MRC-based Medical NER with Multi-task Learning and Multi-strategies.- A Multi-Gate Encoder for Joint Entity and Relation Extraction.- Improving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning.- Machine Translation and Multilingual Information Processing.- Towards Making the Most of Pre-trained Translation Model for Quality Estimation.- Supervised Contrastive Learning for Cross-lingual Transfer Learning.- Minority Language Information Processing.- Interactive Mongolian Question Answer Matching Model Based on Attention Mechanism in the Law Domain.- Language Resource and Evaluation.- TCM-SD: A Benchmark for Probing Syndrome Differentiation via Natural Language Processing.- COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation.- NLP Applications.- Can We Really Trust Explanations? Evaluating the Stability of Feature Attribution Explanation Methods via Adversarial Attack.- Dynamic Negative Example Construction for Grammatical Error Correction using Contrastive Learning.- SPACL: Shared-Private Architecture based on Contrastive Learning for Multi-domain Text Classification.- Low-Resource Named Entity Recognition Based on Multi-hop Dependency Trigger.- Fundamental Analysis based Neural Network for Stock Movement Prediction.