Buch, Englisch, 466 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 733 g
22nd China National Conference, CCL 2023, Harbin, China, August 3-5, 2023, Proceedings
Buch, Englisch, 466 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 733 g
Reihe: Lecture Notes in Artificial Intelligence
ISBN: 978-981-99-6206-8
Verlag: Springer Nature Singapore
The 82 full papers included in this book were carefully reviewed and selected from 278 submissions. They were organized in topical sections as follows: Fundamental Theory and Methods of Computational Linguistics, Information Retrieval, Dialogue and Question Answering, Text Generation, Dialogue and Summarization, Knowledge Graph and Information Extraction, Machine Translation and Multilingual Information Processing, Language Resource and Evaluation, Pre-trained Language Models, Social Computing and Sentiment Analysis, NLP Applications.
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Research
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Fachgebiete
Weitere Infos & Material
Fundamental Theory and Methods of Computational Linguistics.- The Contextualized Representation of Collocation.- Information Retrieval, Dialogue and Question Answering.- Ask to Understand: Question Generation for Multi-hop Question Answering.- Learning on Structured Documents for Conditional Question Answering.- Overcoming Language Priors with Counterfactual Inference for Visual Question Answering.- Rethinking Label Smoothing on Multi-hop Question Answering.- Text Generation, Dialogue and Summarization.- Unsupervised Style Transfer in News Headlines via Discrete Style Space.- Lexical Complexity Controlled Sentence Generation for Language Learning.- Improving Zero-shot Cross-lingual Dialogue State Tracking via Contrastive Learning.- Knowledge Graph and Information Extraction.- Document Information Extraction via Global Tagging.- A Distantly-Supervised Relation Extraction Method Based on Selective Gate and Noise Correction.- Improving Cascade Decoding with Syntax-aware Aggregator and Contrastive Learning for Event Extraction.- TERL: Transformer Enhanced Reinforcement Learning for Relation Extraction.- P-MNER: Cross Modal Correction Fusion Network with Prompt Learning for Multimodal Named Entity Recognitiong.- Self Question-answering: Aspect Sentiment Triplet Extraction via a Multi-MRC Framework based on Rethink Mechanism.- Enhancing Ontology Knowledge for Domain-Specific Joint Entity and Relation Extraction.- Machine Translation and Multilingual Information Processing.- FACT:A Dynamic Framework for Adaptive Context-Aware Translation.- Language Resource and Evaluation.- MCLS: A Large-Scale Multimodal Cross-Lingual Summarization Dataset.- CHED: A Cross-Historical Dataset with a Logical Event Schema for Classical Chinese Event Detection.- Training NLI Models Through Universal Adversarial Attack.- Pre-trained Language Models.- Revisiting k-NN for Fine-tuning Pre-trained Language Models.- Adder Encoder for Pre-trained Language Model.- Exploring Accurate and Generic Simile Knowledge from Pre-trained Language Models.- Social Computing and Sentiment Analysis.- Learnable Conjunction Enhanced Model for Chinese Sentiment Analysis.- Enhancing Implicit Sentiment Learning via the Incorporation of Part-of-Speech for Aspect-based Sentiment Analysis.- Improving Affective Event Classification with Multi-Perspective Knowledge Injection.- NLP Applications.- Adversarial Network with External Knowledge for Zero-Shot Stance Detection.- Few-Shot Charge Prediction with Multi-Grained Features and Mutual Information.- SentBench: Comprehensive Evaluation of Self-Supervised Sentence Representation with Benchmark Construction.
