Atjaunināt sīkdatņu piekrišanu

E-grāmata: Natural Language Processing and Chinese Computing: 12th National CCF Conference, NLPCC 2023, Foshan, China, October 12-15, 2023, Proceedings, Part I

Edited by , Edited by , Edited by , Edited by
Citas grāmatas par šo tēmu:
  • Formāts - PDF+DRM
  • Cena: 130,27 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This three-volume set constitutes the refereed proceedings of the 12th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2023, held in Foshan, China, during October 12–15, 2023.

The 143 regular papers included in these proceedings were carefully reviewed and selected from 478 submissions. They were organized in topical sections as follows: dialogue systems; fundamentals of NLP; information extraction and knowledge graph; machine learning for NLP; machine translation and multilinguality; multimodality and explainability; NLP applications and text mining; question answering; large language models; summarization and generation; student workshop; and evaluation workshop.

Dialogue Systems.- A Task-oriented Dialog Model with Task-progressive
and Policy-aware Pre-training.- Retrieval-Augmented Knowledge-Intensive
Dialogue.- Episode-based Prompt Learning for Any-shot Intent
Detection.- CrossDial: An Entertaining Dialogue Dataset of Chinese
Crosstalk.- Fundamentals of NLP.- Recurrent Transformers for Long Document
Understanding.- SCA-CLS: A New Semantic-Context-Aware Framework for
Community-Oriented Lexical Simplification.- A Cross-lingual Sentiment
Embedding Model with Semantic and Sentiment Joint Learning.- Learning to
Attentively Represent Distinctive Information for Semantic Text
Matching.- Information Extraction and Knowledge Graph.- Reasoning Through
Memorization: Nearest Neighbor Knowledge Graph Embeddings.- MACO: A Modality
Adversarial and Contrastive Framework for Modality-missing Multi-modal
Knowledge Graph Completion.- A Joint Entity and Relation Extraction Approach
Using Dilated Convolution and Context Fusion.- Interest Aware Dual-channel
Graph Contrastive Learning for Session-based Recommendation.- Chinese Event
Causality Identification Based on Retrieval Enhancement.- UZNER: A Benchmark
for Named Entity Recognition in Uzbek.- Evaluation Framework for Poisoning
Attacks on Knowledge Graph Embeddings.- Label-guided Compressed Prototypical
Network for Incremental Few-shot Text Classification.- Auxiliary Information
Enhanced Span-based Model for Nested Named Entity
Recognition.- DialogRE$^{C+}$: An Extension of DialogRE to Investigate How
Much Coreference Helps Relation Extraction in Dialogs.- A Bi-directional
Multi-hop Inference Model for Joint Dialog Sentiment Classification and Act
Recognition.- Positive-guided Knowledge Distillation for Document-level
Relation Extraction with Noisy Labeled Data.- PromptCL: Improving Event
Representation via Prompt Template and Contrastive Learning.- RMGCN: Masked
Graph Convolutional Networks for Relation-Aware Entity Alignment with
Dangling Cases.- SymCoNLL: A Symmetry-based Approach for Document Coreference
Resolution.- What Makes a Charge? Identifying Charge-Discriminative Facts
with Legal Elements.- Machine Learning for NLP.-  A New Encoder Using
Character and Word Feature Fusion for Chinese Math Word Problem
Solving.- MarkBERT: Marking Word Boundaries Improves Chinese BERT.- MCVIE: An
Effective Batch-Mode Active Learning for Multi-Label Text
Classification.- Task-consistent Meta Learning for Low-resource Speech
Recognition.- An Adaptive Learning Method for Solving the Extreme Learning
Rate Problem of Transformer.- Machine Translation and Multilinguality.-
Towards Making the Most of LLM for Translation Quality Estimation.- Towards
Better Translations from Classical to Modern Chinese: A New Dataset and a New
Method.- Imitation Attacks Can Steal More than You Think from Machine
Translation Systems.- Monolingual Denoising with Large Language Models for
Low-Resource Machine Translation.- Multimodality and Explainability.- CAMG:
Context-Aware Moment Graph Network for Multimodal Temporal Activity
Localization via Language.- Semantic Extension for Cross-Modal Retrieval of
Medical Image-Diagnosis Report.- ECOD: A Multi-Modal Dataset for Intelligent
Adjudication of E-Commerce Order Disputes.- Bounding and Filling: A Fast and
Flexible Framework for Image Captioning.- NLP Applications and Text
Mining.- ASKSpell: Adaptive Surface Knowledge Enhances Tokens Semantic
Representations for Chinese Spelling Check.- Biomedical Entity Normalization
Using Encoder Regularization and Dynamic Ranking Mechanism.- Legal Judgment
Prediction Incorporating Guiding Cases Matching.- Punctuation Matters!
Stealthy Backdoor Attack for Language Models.- SeSQL: A High-quality
Large-scale Session-level Chinese Text-to-SQL Dataset.- RSpell:
Retrieval-augmented Framework for Domain Adaptive Chinese Spelling
Check.- Exploiting Multiple Features for Hash Codes Learning with
Semantic-Alignment-Promoting Variational Auto-encoder.- Enhancing Detailed
Feedback to Chinese Writing Learners Using a Soft-Label Driven Approach and
Tag-Aware Ranking Model.- Question Answering.- NAPG: Non-Autoregressive
Program Generation for Hybrid Tabular-Textual Question
Answering.- Mixture-of-Experts for Biomedical Question
Answering.- Fine-grained Question-Answer Matching via Sentence-aware
Contrastive Self-supervised Transfer.- KARN:Knowledge Augmented Reasoning
Network for Question Answering.- Large Language Models.- Creative
Destruction: Can Language Models Interpret Oxymorons?.- Global Prompt Cell: A
Portable Control Module for Effective Prompt Tuning.- What Events Do
Pre-trained Language Models Learn from Text? Probing Event-based Commonsense
Knowledge by ConfidenceSorting.- Revisit Input Perturbation Problems for
LLMs: A Unified Robustness Evaluation Framework for Noisy Slot Filling
Task.- Large Language Models are Diverse Role-Players for Summarization
Evaluation.- COSYWA: Enhancing Semantic Integrity in Watermarking Natural
Language Generation.- Summarization and Generation.- Multi-Step Review
Generation Based on Masked Language Model for Cross-Domain Aspect-Based
Sentiment Analysis.- rT5: A Retrieval-Augmented Pre-Trained Model for Ancient
Chinese Entity Description Generation.- Probing Bilingual Guidance for
Cross-Lingual Summarization.- Accurate, Diverse and Multiple Distractor
Generation with Mixture of Experts.- Improve the Diversity and Novelty for
Open-ended Neural Text Generation via Inverse Probability
Weighting.- Dialogue Systems.- A Unified Generation Approach for Robust
Dialogue State Tracking.- An Explicit-Memory Few-shot Joint Learning
Model.- A Noise-Removal of Knowledge Graph Framework for Profile-based Spoken
Language Understanding.- Bilevel Scheduled Sampling for Dialogue
Generation.- Dial-QP: A Multi-Tasking and Keyword-Guided Approach for
Enhancing Conversational Query Production.- Discourse Relation-Aware
Multi-turn Dialogue Response Generation.