- Against the Clock: Lessons Learned by Applying Temporal Planning in Practice.- A Novel Approach for Leveraging Agent-based Experts on Large Language Models to Enable Data Sharing among Heterogeneous IoT Devices in Agriculture.- An Extensive Empirical Analysis of Macro-Actions for Numeric Planning.- Feature selection on contextual embedding pushing the sparseness.- Neuro-symbolic Integration for Open Set Recognition in Network Intrusion Detection.- MM-IGLU-IT: Multi-Modal Interactive Grounded Language Understanding in Italian.- IDADA: A Blended Inductive-Deductive Approach for Data Augmentation .- HaWANet: Road Scene Understanding with Multi-modal Sensor Data using Height-Width-driven Attention Network.

- Hybrid Classification of European Legislation using Sustainable Development Goals.- Supporting Decision-Making for City Management through Automated Planning and Execution.- NutriWell: an Explainable Ontology-Based FoodAI Service for Nutrition and Health Management.- Regular Clocks for Temporal Task Specifications in Reinforcement Learning.- A Real-Time Support with Haptic Feedback for Safer Driving using Monocular Camera.- Relating explanations with the inductive biases of Deep Graph Networks.- ntegrating Temporal Planning and Knowledge Representation to Generate Personalized Touristic Itineraries.- ASR Systems Under Acoustic Challenges: A Multilingual Study.

- Automating Resume Analysis: Knowledge Graphs via Prompt Engineering.- Combined Text-Visual Attention Models for Robot Task Learning and Execution.- ICE: An Evaluation Metric to Assess Symbolic Knowledge Quality.- Hierarchical Knowledge Extraction from Opaque Machine Learning Predictors.- On Different Symbolic Music Representations for Algorithmic Composition Approaches based on Neural Sequence Models.- DR-Minerva: a Multimodal Language Model based on Minerva for Diagnostic Information Retrieval .- REPAIR platform: Robot-aidEd PersonAlIzed Rehabilitation.- Integrating classical planners with GPT-based Planning Policies.

- Probabilistic Traces in Declarative Process Mining.