The proceedings contain 10 papers. The special focus in this conference is on Discovering Drift Phenomena in Evolving Landscapes. The topics include: CeDFormer: Community Enhanced Transformer for Dynamic Network Embedding; on the Impact of Industrial Delays when Mitigating Distribution Drifts: An Empirical Study on Real-World Financial Systems; Understanding Knowledge Drift in LLMs Through Misinformation; exploring Concept Drift Visualization and Explanation in Image Streams; a Synthetic Benchmark to Explore Limitations of Localized Drift Detections; unsupervised Concept Drift Detection Based on Parallel Activations of Neural Network; unsupervised Assessment of Landscape Shifts Based on Persistent Entropy and Topological Preservation; addressing Temporal Dependence, Concept Drifts, and Forgetting in Data Streams.
Piangerelli, Marco; Prenkaj, Bardh; Rotalinti, Ylenia; Joshi, Ananya; Stilo, Giovanni (Eds.). (2025). Discovering Drift Phenomena in Evolving Landscapes: first International Workshop, DELTA 2024. Springer. Isbn: 978-3-031-82345-9. Isbn: 978-3-031-82346-6. Doi: 10.1007/978-3-031-82346-6.
Discovering Drift Phenomena in Evolving Landscapes: first International Workshop, DELTA 2024
Giovanni Stilo
Supervision
2025
Abstract
The proceedings contain 10 papers. The special focus in this conference is on Discovering Drift Phenomena in Evolving Landscapes. The topics include: CeDFormer: Community Enhanced Transformer for Dynamic Network Embedding; on the Impact of Industrial Delays when Mitigating Distribution Drifts: An Empirical Study on Real-World Financial Systems; Understanding Knowledge Drift in LLMs Through Misinformation; exploring Concept Drift Visualization and Explanation in Image Streams; a Synthetic Benchmark to Explore Limitations of Localized Drift Detections; unsupervised Concept Drift Detection Based on Parallel Activations of Neural Network; unsupervised Assessment of Landscape Shifts Based on Persistent Entropy and Topological Preservation; addressing Temporal Dependence, Concept Drifts, and Forgetting in Data Streams.
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