Ulteriori informazioni
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.
Sommario
.- Language and Foundation Models.
.- Analysis of Large Language Model Prompting and Generation using Toulmin s Model.
.- MultiRAG: An Agentic Multi-modal and Multi-source Retrieval Augmented Generation Framework for Scientific Research.
.- Enhancing RAG System Performance Through Semantic Layout Chunking.
.- Automating Perdurant Meta-Property Assignment using GPT-4.
.- Evaluating Large Language Models for Real-World Engineering Tasks.
.- Generation of Ethical Rules Using Large Language Models.
.- Large Language Models Imitate Logical Reasoning, but at what Cost?.
.- LAPEFT: A Lexicon-Enhanced Approach to Parameter-Efficient Fine-Tuning for Financial News Sentiment Classification.
.- SimLabel: Consistency-Guided OOD Detection with Pretrained Vision-Language Models.
.- RePrompt: Towards Robust Continual Test-Time Adaptation via Replay Prompt for CLIP.
.- Trustworthy and Explainable AI.
.- Probabilistic Lipschitzness and the Stable Rank for Measuring XAI Model Robustness.
.- Graph-based Integrated Gradients for Explaining Graph Neural Networks.
.- Assessing Algorithmic Fairness in Socioeconomic Predictions Using Australian Census Data.
.- TrustGuard: IoT Intrusion Detection with XAI-Driven Feature Refinement for Enhanced Multi-class Edge Classification.
.- PP-Pose: Privacy-Preserving Human Pose Estimation Using Random High-Frequency Channel Combinations.
.- Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Models.
.- Concept Control for LLM Safety Using Radial Basis Function Representations.
.- Prompting Instability: An Empirical Study of LLM Robustness in Code Vulnerability Detection.
.- Requirements-based Explainability for Multi-Agent Systems.
.- On Explaining Proxy Discrimination and Unfairness in Individual Decisions Made by AI Systems.
.- All Models Are Miscalibrated, But Some Less So: Comparing Calibration with Conditional Mean Operators.
.- Whose Side Are You On: Investigating Political Bias of Large Language Models.
.- Guardrails, Not Guesswork: A Framework for Trustworthy AI Adoption.
.- Knowledge Representation and Data Mining.
.- Categorization Architecture with Predictive Reasoning and Alignment for UNSPSC.
.- SVDformer: Direction-Aware Spectral Graph Embedding Learning via SVD and Transformer.
.- Predicting Generalization Error under Graph Distribution Shifts via Parameter Discrepancy with Accumulated Gradient.
.- Predicting Graph Structure via Adapted Flux Balance Analysis.
.- cFedLAD: A Clustered Additive LoRA Framework for Robust and Personalized Federated Learning.
.- Dimensionally Reduced Open-World Clustering: DROWCULA.
.- Noise-Robust Topology Estimation of 2D Image Data via Neural Networks and Persistent Homology.
.- MFiSP: A Multimodal Fire Spread Prediction Framework.
.- Signal Beneath the Surface: A Deep Learning Pipeline for Marine Acoustic Intelligence.
.- Weather Forecasting System Four Seasons in One Day and Shelter Suggestion for Sydney & Melbourne & Canberra.
.- Proactive Air Quality Forecasting and Health Alert System for Melbourne.
.- Solving Partial Graph Matching as a Stable Matching Problem.
Riassunto
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.
