AI 2024: Advances in Artificial Intelligence 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, Melbourne, VIC, Australia, November 25–29, 2024, Proceedings, Part I

This two-volume set LNAI 15442-15443 constitutes the refereed proceedings of the 37th Australasian Joint Conference on Artificial Intelligence, AI 2024, held in Melbourne, VIC, Australia, during November 25-29, 2024.
The 59 full papers presented together with 3 short papers were carefully reviewed and selected from 108 submissions.
Part 1: Knowledge Representation and NLP; Trustworthy and Explainable AI; Machine Learning and Data Mining.
Part 2: Reinforcement Learning and Robotics; Learning Algorithms; Computer Vision; AI for Healthcare.

.- Knowledge Representation and NLP.
.- DELA: Dual Embedding Using LSTM and Attention for Asset Tag Inference in Industrial Automation Systems.
.- Combined Change Operators for Trust and Belief.
.- Highlighting Case Studies in LLM Literature Review of Interdisciplinary System Science.
.- Legal Judgment Prediction through Argument Analysis.
.- Conditional Prototypical Optimal Transport for Enhanced Clue Identification in Multiple Choice Question Answering.
.- REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models.
.- Leveraging LLM in Genetic Programming Hyper-Heuristics for Dynamic Microservice Deployment.
.- Bidirectional Dependency Representation Disentanglement for Time Series Classification.
.- SCODA - A Framework for Software Capability Representation and Inspection.
.- Some Considerations for the Preservation of Endangered Languages Using Low-Resource Machine Translation.
.- Trustworthy and Explainable AI.
.- Improving Intersectional Group Fairness Using Conditional Generative Adversarial Network and Transfer Learning.
.- GPT-4 Attempting to Attack AI-Text Detectors.
.- Charting a Fair Path: FaGGM Fairness-aware Generative Graphical Models.
.- Shedding Light on Greenwashing: Explainable Machine Learning for Green Ad Detection.
.- Beyond Factualism: A Study of LLM Calibration through the Lens of Conversational Emotion Recognition.
.- Ensuring Fairness in Stochastic Multi-Armed Bandit Problems for Effective Group Recommendations.
.- Human Decision-Making Concepts with Goal-Oriented Reasoning for Explainable Deep Reinforcement Learning.
.- Towards Explainable Deep Learning for Non-melanoma Skin Cancer Diagnosis.
.- Machine Learning and Data Mining.
.- Localization System Enhanced with CDLPE: A Low-Cost, Resilient Map-Matching Algorithm.
.- FocDepthFormer: Transformer with latent LSTM for Depth Estimation from Focal Stack.
.- TSI: A Multi-View Representation Learning Approach for Time Series Forecasting.
.- Climate Downscaling Monthly Coastal Sea Surface Temperature Using Convolutional Neural Network and Composite Loss.
.- DBSSM: Deep BERT-based Semantic Skill Matching from Resumes to a Public Skill Taxonomy.
.- Designing an Adaptive AI System for Operation on Board the SpIRIT Nano-satellite.
.- LSTM Autoencoder-based Deep Neural Networks for Barley Genotype-to-Phenotype Prediction.
.- An Improved Prescriptive Tree-based Model for Stochastic Parallel Machine Scheduling.
.- Economic Graph Lottery Ticket: A GNN based Economic Forecasting Model.
.- Pattern-based Trading by Continual Learning of Price and Volume Patterns.
.- An Experimental Study on Decomposition-Based Deep Ensemble Learning for Traffic Flow Forecasting.