Natural Language Processing and Chinese Computing

13th National CCF Conference, NLPCC 2024, Hangzhou, China, November 1–3, 2024, Proceedings, Part III

AvDerek F. Wong,Zhongyu Wei

Häftad, Engelska, 2024

Del 15361 i serien Lecture Notes in Computer Science

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Beskrivning

The five-volume set LNCS 15359 - 15363 constitutes the refereed proceedings of the 13th National CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2024, held in Hangzhou, China, during November 2024.The 161 full papers and 33 evaluation workshop papers included in these proceedings were carefully reviewed and selected from 451 submissions. They deal with the following areas: Fundamentals of NLP; Information Extraction and Knowledge Graph; Information Retrieval, Dialogue Systems, and Question Answering; Large Language Models and Agents; Machine Learning for NLP; Machine Translation and Multilinguality; Multi-modality and Explainability; NLP Applications and Text Mining; Sentiment Analysis, Argumentation Mining, and Social Media; Summarization and Generation.

Produktinformation

Utgivningsdatum:2024-11-01
Mått:155 x 235 x 29 mm
Vikt:809 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:503
Förlag:Springer Verlag, Singapore
ISBN:9789819794362

Utforska kategorier

Systemvetenskap och AI inom Data och IT

Innehållsförteckning

Improving Causal Inference of Large Language Models with SCM Tools.- A Privacy-Preserving Framework for Medical Chatbot based on LLM with Retrieval Augmented Generation.- Regularized Continual Learning for Large-Scale Language Models via Probing.- LasQ: Largest Singular Components fine-tuning for LLMs with Quantization.- MultiAICL: Multi-Task Tuning for Augmented In-Context Learning in Text Style Transfer.- What is the best model? Application-driven Evaluation for Large Language Models.-Sparse Mixture of Experts Language Models Excel in Knowledge Distillation.- Evaluation and Analysis of the Chinese Semantic Dependency Understanding Ability of Large Language Models.- Reparameterization-based Parameter-Efficient Fine-Tuning Methods for Large Language Models: A Systematic Survey.- SACL: Sequential Augmentation with Curriculum Learning in Dataset Level.- Classifiers Guided Controllable Text Generation for Discrete Diffusion Language Models.- AugMixSpeech: A Data Augmentation Method and Consistency Regularization for Mandarin Automatic Speech Recognition.- FIRP: Faster LLM inference via future intermediate representation prediction.- Margin Discrepancy-based Adversarial Training for Multi-Domain Text Classification.- Effective Knowledge Graph Embedding with Quaternion Convolutional Networks.- Improving End-to-End Speech Translation with Progressive Dual Encoding.- Assessing Translation Quality of Hypotactic Structure for Chinese-to-English Machine Translation.- Understanding and Improving Low-Resource Neural Machine Translation with Shallow Features.- Improving Non-autoregressive Machine Translation with Error Exposure and Consistency Regularization.- Neural Chat Translation as Online Document-to-Document Translation.- Autogenerated MQM Data for Quality Estimation based on Sequence Labeling.- Pruning Residual Networks in Multilingual Neural Machine Translation to Improve Zero-shot Translation.- Leveraging Parameter-Efficient Fine-Tuning for Multilingual Abstractive Summarization.- Improving Automatic Post-editing with Error Prompts Extracted from Quality Estimation.- Progressive and Consistent Subword Regularization for Neural Machine Translation.- Language-Emphasized Cross-Lingual In-Context Learning for Multilingual LLM.- A Multilevel Interaction Network Framework for Multimodal Entity Linking.- Evaluating the Fidelity of Image Captioning via Weighted Boolean Question Answering.- Optimized Conversational Gesture Generation with Enhanced Motion Feature Extraction and Cascaded Generator.- Exploring the Potential of Prompting Methods in Low-resource Speech Recognition with Whisper.- RAVL: A Retrieval-Augmented Visual Language Model Framework for Knowledge-Based Visual Question Answering.- ASRLM: ASR-Robust Language Model Pre-Training via Generative and Discriminative learning.- DFS-QA: Dynamic Frame Selection for Better Video Question Answering.- Deep Foreground-Background Weighted Cross-Modal Hashing.- Graph Interpretation of Image-Text matching: Link Prediction on Concept-Enhanced Cross-Modal Graph.- Multi-Granularity Semantic Guided Transformer for Radiology Report Generation.- Steganographic Text Generation Based on Large Language Models in Dialogue Scenarios.- A Novel ICD Coding Method Based on Associated and Hierarchical Code Description Distillation.