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El. knyga: Chinese Computational Linguistics: 22nd China National Conference, CCL 2023, Harbin, China, August 3-5, 2023, Proceedings

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Chinese Computational Linguistics: 22nd China National Conference, CCL 2023, Harbin, China, August 3-5, 2023, ProceedingsDidesnis paveikslėlis
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This book constitutes the refereed proceedings of the 22nd China National Conference on Chinese Computational Linguistics, CCL 2023, Harbin, China, August 35, 2023. 

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.

 
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.
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