Natural Language Processing and Chinese Computing : 14th National CCF Conference, NLPCC 2025, Urumqi, China, August 7–9, 2025, Proceedings, Part III / edited by Xian-Ling Mao, Zhaochun Ren, Muyun Yang.

Format:

• Book

Author/Creator:

• Mao, Xian-Ling.

Series:

• Lecture Notes in Artificial Intelligence, 2945-9141 ; 16104

Language:

English

Subjects (All):

• Artificial intelligence.
• Natural language processing (Computer science).
• Artificial Intelligence.
• Natural Language Processing (NLP).

Local Subjects:

• Artificial Intelligence.
• Natural Language Processing (NLP).

Physical Description:

1 online resource (1033 pages)

Edition:

1st ed. 2026.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2026.

Summary:

The four-volume set LNAI 16102 - 16105 constitutes the refereed proceedings of the 14th CCF National Conference on Natural Language Processing and Chinese Computing, NLPCC 2025, held in Urumqi, China, during August 7–9, 2025. The 152 full papers and 26 evaluation workshop papers included in these proceedings were carefully reviewed and selected from 505 submissions. They were focused on the following topical sections: Part I : Information Extraction and Knowledge Graph & Large Language Models and Agents. Part II : Multimodality and Explainability & NLP Applications / Text Mining. Part III : IR / Dialogue Systems / Question Answering; Machine Translation and Multilinguality & Sentiment analysis / Argumentation Mining / Social Media. Part IV : Machine Learning for NLP; Fundamentals of NLP; Summarization and Generation; Others & Evaluation Workshop.

Contents:

• IR / Dialogue Systems / Question Answering
• TriG-RAG: Triple-Granularity Fusion for Retrieval-Augmented Generation with Adaptive Context-Relation Balance.
• Knowledge Distillation for Large Language Models Based on Global Keywords and Chain of Thought.
• Exploring the Capabilities of Chinese LLMs in the Legal Field.
• RoleplayLLM: Enhancing Role-Playing Abilities in Large Language Models via Multidimensional Fine Tuning and Preference Optimization.
• Multi-task Contrastive Learning Enhanced Instruction Tuning for Dialog Understanding.
• DynaRAG: Adaptive Context Compression via Reinforcement Learning for Enhanced Retrieval-Augmented Generation.
• Retrieving and Reading Multimodal Documents for Knowledge-based VQA.
• Relation-Aware Graph Reasoning for Multiple Choice Question Answering.
• Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Tracking.
• ReD-RAG: Rewritable Decomposition-Guided Iterative Retrieval Augmented Generation for Open Domain Multi-Hop Reasoning.
• Bridging Questions and Charts: A Weakly Supervised Alignment Model for Chart Question Answering.
• FRAG: Focused Retrieval Augmented Generation Reducing Retrieval Scope by Mapping Table.
• Ensuring Context Completeness in Retrieval-Augmented Generation for Knowledge-Intensive Question-answering.
• Machine Translation and Multilinguality
• Improving LLM-based Document-level MT with Multi-Knowledge Fusion.
• Continual Learning for Multilingual Neural Machine Translation via Meta-Contrastive Memory Replay.
• Prompting and Consistency Learning Strategies for Multimodal Grammatical Error Correction in Low Error Density Domains.
• Bias Beyond English: Evaluating Social Bias and Debiasing Methods in a Low-Resource Setting.
• Doc-Guided Sent2Sent++: A Sent2Sent++ Agent with Doc-Guided memory for Document-level Machine Translation.
• Fine-Grained Contrastive Learning for End-to-End Vietnamese Text Image Machine Translation.
• Adaptive Inner Speech Text Alignment for LLM-based Speech Translation.
• Fine-Tuning for Low-Resource Language Machine Translation Using Large Language Models Integrated with Dependency Parsing Rule.
• Simplify Translate: A Unified Framework for Accessible Machine Translation.
• PGATA: Phonology-and-Glyph-Aware Token Alignment for Transfer Learning in Cantonese Sarcasm Detection.
• LLM-enhanced Translation for Low-resource Languages: Cross-lingual Alignment and Multi-domain Adaptation.
• Sentiment analysis / Argumentation Mining / Social Media
• Best-Fit Document: Enhancing Compositional Generalization in Multi-label Text Classification.
• Dialogue Multi-dimensional Feature Dividing and Fusion Model for Dialogue Aspect-based Sentiment Quadruple Analysis.
• Boosting Affective Events Classification: A Contextual Framework with Chain-of-Thought Prompt.
• Hate Speech Detection in Somali-English Code-Switched Texts.
• Chinese Spelling Correction for Social-Platform Internet Slang Texts.
• DiGTF: A Difference-Guided Two-Stage Fusion Framework for Multimodal Sentiment Analysis.
• EVL-MCoT: Enhanced Vision-Language Multi-CoT for Harmful Meme Detection.
• Deep Graph Neural Point Process For Learning Temporal Interactive Networks.
• Bayesian Network-based Adaptive Prompt Learning for Emotion-Cause Pair Extraction.
• Exploring Sentiment Analysis in Tigrigna: Insights from Social Media Texts.
• Unlocking the Advantage of Context Interaction via Bi-Graph Reasoning for Document-level Aspect-based Sentiment Analysis.
• EMAO: Expectation-Maximization and Adaptive Objective for Microscopic Cascade Prediction.
• Attributed Graph Clustering with Dual Contrastive Regularization.
• Deep Learning-Based Knowledge Injection for Metaphor Detection: A Comprehensive Review.
• CADA: A Counterfactual Adversarial Data Augmentation Framework for Low-Resource Hate Speech Detection.
• Semantic Information Enhanced Fake News Detection.
• Fine-grained Inappropriate Speech Detection Based on Momentum Contrastive Learning.
• ISIPN: Intention-Semantic Incongruity Perception Network for Multimodal Metaphor Detection.
• Self-Distillation Across Modalities: Enhancing Cross-Modal Correlation Perception for Multimodal Fake News Detection.
• D-PathVER: Dynamic Reasoning Paths for Complex Claim Verification.
• Dynamic Multi-Views In-Context Learning with Large Language Models for Aspect-Based Sentiment Analysis.
• MAGI: Modality-Aligned Geometry-aware Integration for Robust Multimodal Sentiment Analysis.

ISBN:

9789819533497