Skip to main content
Springer Nature Link
Account

AI 2025: Advances in Artificial Intelligence

38th Australasian Joint Conference on Artificial Intelligence, AI 2025, Canberra, ACT, Australia, December 1–5, 2025, Proceedings, Part I

  • Conference proceedings
  • © 2026

Overview

Editors:
  1. Miaomiao Liu

    1. Australian National University, Canberra, Australia

  2. Xin Yu

    1. University of Queensland, St Lucia, Australia

  3. Chang Xu

    1. University of Sydney, Sydney, Australia

  4. Yiliao Song

    1. Adelaide University, Adelaide, Australia

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 16370)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: AI 2025.

  • 12k Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

About this book

This two-volume set LNAI 16370-16371 constitutes the refereed proceedings of the 38th Australasian Joint Conference on Artificial Intelligence, AI 2025, held in Canberra, ACT, Australia, during December 1–5, 2025.

The 73 full papers presented together with 1 short papers were carefully reviewed and selected from 152 submissions. They were organized in following topical section:

Part I :  Language and Foundation Models and Knowledge Representation and Data Mining,

Part II : Learning Algorithms, Computer Vision, AI for Healthcare and  Reinforcement Learning and Robotics.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, books and news in related subjects.

Table of contents (36 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Language and Foundation Models

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Analysis of Large Language Model Prompting and Generation Using Toulmin’s Model

      • Geordie Dalzell, Chen Liu, Wei Peng, Xinghuo Yu
      Pages 3-14

    3. MultiRAG: An Agentic Multi-Modal and Multi-Source Retrieval-Augmented Generation Framework for Scientific Research

      • Ziqiu Huang, Xiang Li, Wenli Yang, Quan Bai, David Green, Clive McMahon
      Pages 15-27

    4. Enhancing RAG System Performance Through Semantic Layout Chunking

      • Man Qin, Qiang Sun, Tim French, Wei Liu
      Pages 28-39

    5. Automating Perdurant Meta-Property Assignment Using GPT-4

      • Shathika Kularatne, Matt Selway, Wolfgang Mayer, Markus Stumptner
      Pages 40-53

    6. Evaluating Large Language Models for Real-World Engineering Tasks

      • René Heesch, Sebastian Eilermann, Alexander Windmann, Alexander Diedrich, Oliver Niggemann
      Pages 54-66

    7. Generation of Ethical Rules Using Large Language Models

      • Tammy Zhong, Yang Song, Maurice Pagnucco
      Pages 67-79

    8. Large Language Models Imitate Logical Reasoning, but at What Cost?

      • Lachlan McGinness, Peter Baumgartner
      Pages 80-96

    9. LAPEFT: A Lexicon-Enhanced Approach to Parameter-Efficient Fine-Tuning for Financial News Sentiment Classification

      • Hang Nguyen, John Le, Chau Nguyen, Thanh Le, Thai T. Vu
      Pages 97-109

    10. SimLabel: Consistency-Guided OOD Detection with Pretrained Vision-Language Models

      • Shu Zou, Xinyu Tian, Qinyu Zhao, Zhaoyuan Yang, Jing Zhang
      Pages 110-121

    11. RePrompt: Towards Robust Continual Test-Time Adaptation via Replay Prompt for CLIP

      • Ran Wang, Hua Zuo, Ling Chen, Huan Huo, Jie Lu
      Pages 122-133

  3. Trustworthy and Explainable AI

    1. Front Matter

      Pages 135-135
      Download chapter PDF

    2. Probabilistic Lipschitzness and the Stable Rank for Measuring XAI Model Robustness

      • Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
      Pages 137-149

    3. Graph-Based Integrated Gradients for Explaining Graph Neural Networks

      • Lachlan Simpson, Kyle Millar, Adriel Cheng, Cheng-Chew Lim, Hong Gunn Chew
      Pages 150-162

    4. Assessing Algorithmic Fairness in Socioeconomic Predictions Using Australian Census Data

      • Shahadat Uddin, Yajie Huang, Shanshan Fang, Haohui Lu
      Pages 163-176

    5. TrustGuard: IoT Intrusion Detection with XAI-Driven Feature Refinement for Enhanced Multi-class Edge Classification

      • Nimesha Dilini, Nan Sun, Sky Miao, Nour Moustafa
      Pages 177-190

    6. PP-Pose: Privacy-Preserving Human Pose Estimation Using Random High-Frequency Channel Combinations

      • Houke Zhao, Huaxi Huang, Xun Li
      Pages 191-203

    7. Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models

      • Xushuo Tang, Yi Ding, Zhengyi Yang, Yin Chen, Yongrui Gu, Wenke Yang et al.
      Pages 204-219

    8. Concept Control for LLM Safety Using Radial Basis Function Representations

      • Mark Amos, Yang Song, Maurice Pagnucco
      Pages 220-232
Back to top

Other volumes

  1. AI 2025: Advances in Artificial Intelligence

  2. AI 2025: Advances in Artificial Intelligence

Editors and Affiliations

  • Australian National University, Canberra, Australia

    Miaomiao Liu

  • University of Queensland, St Lucia, Australia

    Xin Yu

  • University of Sydney, Sydney, Australia

    Chang Xu

  • Adelaide University, Adelaide, Australia

    Yiliao Song

Accessibility Information

PDF accessibility summary

This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub.

EPUB accessibility summary

This ebook is designed with accessibility in mind, aiming to meet the ePub Accessibility 1.0 AA and WCAG 2.2 Level AA standards. It features a navigable table of contents, structured headings, and alternative text for images, ensuring smooth, intuitive navigation and comprehension. The text is reflowable and resizable, with sufficient contrast. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com.

Bibliographic Information

Keywords

Publish with us

Policies and ethics

Back to top