December 2025, Volume 27, Issue 2

December 2025, Volume 27, Issue 2

  • Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AI [1]
  • Mapping Deep Learning to Blockchain Security: A Survey [13]
  • Urban Planning in the Age of Agentic AI: Emerging Paradigms and Prospects [35]
  • LTSM-Bundle: A Toolbox and Benchmark on Large Language Models for Time Series Forecasting [43]
  • Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape [62]
  • Towards Uncovering How Large Language Models Work: An Interpretability Perspective [79]
  • Unifying Knowledge in Agentic LLMs: Concepts, Methods, and Recent Advancements [88]
  • Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks [97]
  • OmniRouter: Budget and Performance Controllable Multi-LLM Routing [107]
  • Introduction to The Special Section on Safe AI [117]
  • Assuring the Case: A Safety Engineering Approach to AI-Enabled Systems [124]
  • DT-sampler: A SAT-based Decision Tree Ensemble [132]
  • SpaCE-VAE: Sparse and Confident Explanations using Variational Autoencoders [142]
  • Explaining Embedding-Based Matching of Hand-Drawn Binary Symbols with Grad-CAM: A Case Study on Cattle Brands [149]
  • A Non-Parametric Bayesian Approach Towards Online Sequence Learning [156]

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June 2025, Volume 27, Issue 1

June 2025, Volume 27, Issue 1

  • DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models [1]
  • AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models [10]
  • Is Less Really More? Fake News Detection with Limited Information [20]
  • The b2biers System: A Content-Based Perspective on Maximizing Influence and Subscription in Social Networks [32]
  • Dual-Target Disjointed Cross-Domain Recommendation Mediated via Latent User Preferences [52]
  • MoralBench: Moral Evaluation of LLMs [62]
  • Frugal AI: Introduction, Concepts, Development and Open Questions [72]
  • Advancing Table Understanding of Large Language Models via Feature Re-ordering [112]
  • Neural-Symbolic Reasoning over Knowledge Graphs: A Survey from a Query Perspective [124]
  • Span-Oriented Information Extraction: A Unified Framework. [137]

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December 2024, Volume 26, Issue 2

December 2024, Volume 26, Issue 2

  • Blockchain for Large Language Model Security and Safety: A Holistic Survey [1]
  • Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges [21]
  • Exploring Large Language Models for Feature Selection: A Data-centric Perspective [44]
  • Causal inference under limited outcome observability: A case study with Pinterest Conversion Lift [54]
  • DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models [60]
  • FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models [76]
  • Graph Fairness via Authentic Counterfactuals: Tackling Structural and Causal Challenges. [89]
  • FG-SMOTE: Towards Fair Node Classification with Graph Neural Network. [99]
  • Time Series Forecasting with LLMs: Understanding and Enhancing Model Capabilities [109]

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June 2024, Volume 26, Issue 1

June 2024, Volume 26, Issue 1

  • Higher-Order Networks Representation and Learning: A Survey [1]
  • Synthetic data for learning-based knowledge discovery [19]
  • The Case for Hybrid Multi-Objective Optimisation in High-Stakes Machine Learning Applications [24]
  • Fairness in Large Language Models: A Taxonomic Survey [34]
  • Analyzing and explaining privacy risks on time series data: ongoing work and challenges [49]

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December 2023, Volume 25, Issue 2

December 2023, Volume 25, Issue 2

  • An interview with Dr. Jure Lesvek, Winner of ACM SIGKDD 2023 Innovation Award [1]
  • Marginal Nodes Matter: Towards Structure Fairness in Graphs [4]
  • Fighting Fire with Fire: Can ChatGPT Detect AI-generated Text? [14]
  • Storage Systems: Organization, Performance, Coding, Reliability, and Their Data Processing, 1st Edition, October 13, 2021 [22]
  • Report on the 3rd International Workshop on Learning to Quantify (LQ 2023) [25]
  • Anomaly Detection using Generative Adversarial Networks [29]
  • Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs [42]

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