AI 2025: Advances in Artificial Intelligence
Springer Verlag, Singapore
978-981-95-4968-9 (ISBN)
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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.
.- 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.
| Erscheinungsdatum | 25.11.2025 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | 103 Illustrations, color; 15 Illustrations, black and white |
| Verlagsort | Singapore |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Netzwerke | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | computer vision • Data Mining • Deep learning • Explainable machine learning • Human-Computer interaction • Knowledge Representation • Large language model • machine learning • Natural Language Processing • Neural networks • Optimization • Reinforcement Learning • Trustworthy Machine Learning |
| ISBN-10 | 981-95-4968-X / 981954968X |
| ISBN-13 | 978-981-95-4968-9 / 9789819549689 |
| Zustand | Neuware |
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