UID:
almahu_9949931132502882
Format:
XXV, 465 p. 143 illus., 126 illus. in color.
,
online resource.
Edition:
1st ed. 2025.
ISBN:
9789819601196
Series Statement:
Lecture Notes in Artificial Intelligence, 15282
Content:
The five-volume proceedings set LNAI 15281-15285, constitutes the refereed proceedings of the 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, held in Kyoto, Japan, in November 18-24, 2024. The 145 full papers and 35 short papers included in this book were carefully reviewed and selected from 543 submissions. The papers are organized in the following topical sections: Part I: Machine Learning, Deep Learning Part II: Deep Learning, Federated Learning, Generative AI, Natural Language Processing, Large Language Models, Part III: Large Language Models, Computer Vision Part IV: Computer Vision, Autonomous Driving, Agents and Multiagent Systems, Knowledge Graphs, Speech Processing, Optimization Part V: Optimization, General Applications, Medical Applications, Theoretical Foundations of AI.
Note:
-- Deep Learning. -- STLB-GN: Spatio-Temporal Dual Graph Network with Learnable Bases. -- Rethinking the Reliability of Post-hoc Calibration Methods under Subpopulation Shift. -- Zero-shot Heterogeneous Graph Embedding via Semantic Extraction. -- TG-PhyNN: An Enhanced Physically-Aware Graph Neural Network framework for forecasting Spatio-Temporal Data. -- Stock Market Index Movement Prediction using Partial Contextual Embedding BERT-LSTM. -- SCBC: A Supervised Single-cell Classification Method Based on Batch Correction for ATAC-seq Data. -- TS-CATMA: A Lung Cancer Electronic Nose Data Classification Method Based on Adversarial Training and Multi-Scale Attention. -- Visualizing the Unseen: Arabic Image-to-Story Generation Using Deep Learning Techniques. -- Federated Learning. -- Federated Prompt Tuning: When is it Necessary?. -- Dirichlet-Based Local Inconsistency Query Strategy for Active Domain Adaptation. -- FedSD: Cross-Heterogeneous Federated Learning Based on Self-Distillation. -- Personalized Federated Learning with Feature Alignment via Knowledge Distillation. -- Multi-Party Collaborative Hate Speech Study on Social Media via Personalized Federated Learning. -- Preserving Individual User's Right to be Forgotten in Enterprise-Level Federated Learning. -- Generative AI. -- Dance Generation From Music with Enhanced Beat. -- Contrastive Prototype Network for Generative Zero-Shot learning. -- Steganography: An improved robust model for deep hidden network. -- Human- and AI-Generated Marketing Content Comparison Corpus, Evaluation, and Detection. -- Natural Language Processing. -- Mongolian-Chinese Cross-lingual Topic Detection Based on Knowledge Distillation and Contrastive Learning Methods. -- Emergence of Grounded Language Representations for Continuous Object Properties through Decentralized Embodied Learning. -- AI-facilitation for consensus-building by virtual discussion using large language models. -- False Positive Detection for Text-based Person Retrieval. -- An End-to-End Method for Chinese Spelling Error Detection and Correction. -- Dialogue Summarization based on Feature Extraction and Commonsense Injection. -- SPA: Towards A Computational Friendly Cloud-Base and On-Devices Collaboration Seq2seq -- Personalized Generation with Causal Inference. -- Document-Level Relation Extraction Model Based On Boundary Distance Loss And Long-Tail Relation Enhancement. -- MCQG: Reading Comprehension Multiple Choice Questions Generation based on Pre-trained Language Models. -- ZeFaV: Boosting Large Language Models for Zero-shot Fact Verification. -- EC-PEFT: An Expertise-Centric Parameter-Efficient Fine-Tuning Framework for Large Language Models. -- Enhanced Classification of Delay Risk Sources in Road Construction Using Domain- Knowledge-Driven. -- Modeling the Structural and Semantic Features for Japanese Lyrics Generation of J-pop Songs. -- FINE-LMT: Fine-grained Feature Learning for Multi-Modal Machine Translation. -- Segmentation Strategies and Data Enrichment for Improved Abstractive Summarization of Burmese Language. -- Constrained Reasoning Chains for Enhancing Theory-of-Mind in Large Language Models. -- Spatial-Temporal Union Channel Enhancement for Continuous Sign Language Recognition. -- KLoB: a Benchmark for Assessing Knowledge Localization Methods in Language Models. -- Cross-lingual Entity Alignment Model based on Multi-entity Enhancement and Semantic Information. -- Large Language Models. -- A Decomposed-Distilled Sequential Framework for Text-to-Table Task with LLMs. -- Are Dense Retrieval Models Few-Shot Learners?. -- An Empirical Study of Leveraging PLMs and LLMs for Long-Text Summarization. -- A Novel MLLMs-based Two-stage Model for Zero-shot Multimodal Sentiment Analysis. -- DeepTTS: Enhanced Transformer-Based Text Spotter via Deep Interaction Between Detection and Recognition Tasks.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9789819601189
Additional Edition:
Printed edition: ISBN 9789819601202
Language:
English
DOI:
10.1007/978-981-96-0119-6
URL:
https://doi.org/10.1007/978-981-96-0119-6
