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Coles PRICAI 2025: Trends Artificial Intelligence: 22nd Pacific Rim International Conference on Intelligence, 2025, Wellington, New Zealand, November 17-21, Proceedings at Bayshore Shopping Centre in Ottawa, ON
PRICAI 2025: Trends Artificial Intelligence: 22nd Pacific Rim International Conference on Intelligence, 2025, Wellington, New Zealand, November 17-21, Proceedings
PRICAI 2025: Trends Artificial Intelligence: 22nd Pacific Rim International Conference on Intelligence, 2025, Wellington, New Zealand, November 17-21, Proceedings in Ottawa, ON
PRICAI 2025: Trends Artificial Intelligence: 22nd Pacific Rim International Conference on Intelligence, 2025, Wellington, New Zealand, November 17-21, Proceedings in Ottawa, ON
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The five-volume proceedings set LNAI 16451-16456, constitutes the refereed proceedings of the 22nd Pacific Rim International Conference on Artificial Intelligence, PRICAI 2025, held in Wellington, New Zealand, in November 17–21, 2025.
The 197 full papers and 89 short papers included in this book were carefully reviewed and selected from 679 submissions.
The papers are organized in the following topical sections:
Part I:Clustering, Representation Learning, and Learning Systems; Deep learning; Graph learning
Part II: Evolutionary Learning, Transfer and Continual Learning; Real-world Applications
Part III: Human-Centric AI; Large Language Models
Part IV: Interpretability, Fairness, and Trustworthy AI; Multi-Agent; Natural Language Processing; Planning, Scheduling, and Optimisation
Part V: Computer Vision; Time Series Analysis
The five-volume proceedings set LNAI 16451-16456, constitutes the refereed proceedings of the 22nd Pacific Rim International Conference on Artificial Intelligence, PRICAI 2025, held in Wellington, New Zealand, in November 17–21, 2025.
The 197 full papers and 89 short papers included in this book were carefully reviewed and selected from 679 submissions.
The papers are organized in the following topical sections:
Part I:Clustering, Representation Learning, and Learning Systems; Deep learning; Graph learning
Part II: Evolutionary Learning, Transfer and Continual Learning; Real-world Applications
Part III: Human-Centric AI; Large Language Models
Part IV: Interpretability, Fairness, and Trustworthy AI; Multi-Agent; Natural Language Processing; Planning, Scheduling, and Optimisation
Part V: Computer Vision; Time Series Analysis
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