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Language Models for Data-to-Text Problems” and involves the study of technical methods and approaches for adapting large language models to tasks mixing text and structured data, such as statistical report
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) explainability for autonomous systems (Optional) Experience with simulation environments (e.g., CARLA) or multimodal/LVLM models LanguageRequiremets: Applicants must demonstrate at least B2-level proficiency in
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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-connectivity Communication system modelling, performance analysis, and simulation. Optimization tools and machine learning techniques. Hands-on experience with software-defined radios (SDRs) and/or
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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Large vision–language models (LVLMs) can describe driving scenes and support decisions [Li25], but they sometimes hallucinate objects, relations, or events that are not present [Liu24,Liu25]. In a
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malicious behaviors implemented in Smali code. Adversarial attack development: you will design and implement adversarial attacks by manipulating localized malicious payloads against malware detection models
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research focused on biomedical image computing. Our work involves developing state-of-the-art methods for image segmentation, detection, classification, predictive modelling, and image enhancement. We aim
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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one-fits-all model was proven unsuccessful. Large Language Models (LLMs) and knowledge graph models are expected to harmonize the formats and semantics but there are many open questions about their