Natural Language Processing and Chinese Computing

Overcoming Rigid and Monotonous: Enhancing Knowledge-grounded Conversation Generation via Multi-granularity Knowledge.- Learning to Generate Style-Specific Adapters for Stylized Dialogue Generation.- Hierarchical Knowledge Aggregation for Personalized Response Generation in Dialogue Systems.- Multi-hop Reading Comprehension Model Based on Abstract Meaning Representation and Multi-task Joint Learning.- Leveraging Large Language Models for QA Dialogue Dataset Construction and Analysis in Public Services.- MCFC: A Momentum-Driven Clicked Feature Compressed Pre-trained Language Model for Information Retrieval.- Integrating Syntax Tree and Graph Neural Network for Conversational Question Answering over Heterogeneous Sources.- PqE: Zero-Shot Document Expansion for Dense Retrieval with Large Language Models.- CKF: Conditional Knowledge Fusion Method for CommonSense Question Answering.- MPPQA: Structure-Aware Extractive Multi-Span Question Answering for Procedural Documents.- GraphLLM: A General Framework for Multi-hop Question Answering over Knowledge Graphs using Large Language Models.- Local or Global Optimization for Dialogue Discourse Parsing.- Structure and Behavior Dual-Graph Reasoning with Integrated Key-Clue Parsing for Multi-Party Dialogue Reading Comprehension.- Enhancing Emotional Support Conversation with Cognitive Chain-of-Thought Reasoning.- A Simple and Effective Span Interaction Modeling Method for Enhancing Multiple Span Question Answering.- FacGPT:An Effective and Efficient method for Evaluating Knowledge-based Visual Question Answering.- PAPER: A Persona-Aware Chain-of-Thought Learning Framework for Personalized Dialogue Response Generation.- Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Models.- Model-Agnostic Knowledge Distillation between Heterogeneous Models.- Exploring Multimodal Information Fusion in Spoken Off-Topic Degree Assessment.- Integrating Hierarchical Key Information and Semantic Difference Features for Long Text Matching.- CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing.- W2CL:A Multi-task Learning Approach to Improve Domain-Specific Sentence Classification through Word Classification and Contrastive Learning.- Outperforming Larger Models on Text Classification Through Continued Pre-Training.- Semantic Knowledge Enhanced and Global Pointer Optimized Method for Medical Nested Entity Recognition.- CSLAN: A Novel Lexicon Attention Network for Chinese NERS2D: Enhancing Zero-shot Cross-lingual Event Argument Extraction with Semantic Knowledge.- Bias-Rectified Multi-way Learning with Data Augmentation for Implicit Discourse Relation Recognition.- Retrieval-enhanced Template Generation for Template Extraction.- Chinese Named Entity Recognition Based on Template and Contrastive Learning.- Enhancing Logical Rules Based on Self-Distillation for Document-Level Relation ExtractionPrompt-based Joint Contrastive Learning for Zero-Shot Relation ExtractionLow-Resource Event Causality Identification With Global Consistency Constraints.- Only One Relation Possible? Modeling the Ambiguity in Temporal Relation Extraction.- Empowering LLMs for Long-text Information Extraction in Chinese Legal Documents.- LLMADR: A Novel Method for Adverse Drug Reaction Extraction Based on Style Aligned Large Language Models Fine-tuning.- Research on Named Entity Recognition in Ancient Chinese Based on Incremental Pre-training and Domain Lexicon.- MCKRL: A Multi-Channel based Multi-Graph Knowledge Representation Learning Model.