mlsanityData to 7 Oct 2026

Generative AI in EU Law: Liability, Privacy, Intellectual Property, and Cybersecurity

arXiv 2401.07348 ↗First posted 14 Jan 2024cs.CY cs.AIcited by 21

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Abstract (arXiv)

The advent of Generative AI, particularly through Large Language Models (LLMs) like ChatGPT and its successors, marks a paradigm shift in the AI landscape. Advanced LLMs exhibit multimodality, handling diverse data formats, thereby broadening their application scope. However, the complexity and emergent autonomy of these models introduce challenges in predictability and legal compliance. This paper delves into the legal and regulatory implications of Generative AI and LLMs in the European Union context, analyzing aspects of liability, privacy, intellectual property, and cybersecurity. It critically examines the adequacy of the existing and proposed EU legislation, including the Artificial Intelligence Act (AIA) draft, in addressing the unique challenges posed by Generative AI in general and LLMs in particular. The paper identifies potential gaps and shortcomings in the legislative framework and proposes recommendations to ensure the safe and compliant deployment of generative models, ensuring they align with the EU's evolving digital landscape and legal standards.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 36 of its 103 references that are in the map. First posted on arXiv 14 Jan 2024.

Builds on

36 of 103 references.

References · 36

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  1. 2024A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Modelscited by 266
  2. 2022Predictability and Surprise in Large Generative Modelscited by 209
  3. 2022What Does it Mean for a Language Model to Preserve Privacy?cited by 194
  4. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 10; 2026: 3.

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  1. 2024Large Language Models for Cyber Security: A Systematic Literature Reviewcited by 65
  2. 2024XAI meets LLMs: A Survey of the Relation between Explainable AI and Large Language Modelscited by 23
  3. 2025T2I-RiskyPrompt: A Benchmark for Safety Evaluation, Attack, and Defense on Text-to-Image Modelcited by 16
  4. 2024Prompt Obfuscation for Large Language Modelscited by 10
  5. 2025Robustness and Cybersecurity in the EU Artificial Intelligence Actcited by 10
  6. 2025A Comprehensive Survey on Legal Summarization: Challenges and Future Directionscited by 6
  7. 2024Synthetic Lyrics Detection Across Languages and Genrescited by 4
  8. 2024Large Language Model for Patent Concept Generationcited by 4
  9. 2025Who Owns the Output? Bridging Law and Technology in LLMs Attributioncited by 4
  10. 2025Let's have a chat with the EU AI Actcited by 2
  11. 2024The Role of Language Models in Modern Healthcare: A Comprehensive Reviewcited by 1
  12. 2024Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMscited by 1
9 more
  1. 2026Beyond Abstract Compliance: Operationalising trust in AI as a moral relationshipcited by 1
  2. 2024Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acaciascited by 0
  3. 2025It's complicated. The relationship of algorithmic fairness and non-discrimination provisions for high-risk systems in the EU AI Actcited by 0
  4. 2025Synthetic media and computational capitalism: towards a critical theory of artificial intelligencecited by 0
  5. 2025NLP Meets the World: Toward Improving Conversations With the Public About Natural Language Processing Researchcited by 0
  6. 2025Trustworthiness of Legal Considerations for the Use of LLMs in Educationcited by 0
  7. 2025MarkTune: Improving the Quality-Detectability Trade-off in Open-Weight LLM Watermarkingcited by 0
  8. 2026Quantize with Confidence? An Empirical Study of Quantization for Code Generationcited by 0
  9. 2026Protecting patient privacy in clinical foundation models: Technical and legal perspectivescited by 0