Project description
Combining LLMs and neuro-symbolic AI to revolutionise AI solutions
In recent years, advances in ΑΙ – especially large language models (LLMs) – have brought these technologies to the forefront and enabled their use across a growing number of fields. While LLMs offer numerous benefits, they also pose critical challenges, including security vulnerabilities, regulatory and ethical concerns, and the risk of hallucinations. Supported by the Marie Skłodowska-Curie Actions programme, the THIRDWAVE project is building an international, interdisciplinary network to advance LLM-driven neuro-symbolic AI. By combining the strengths of LLMs with symbolic AI, THIRDWAVE aims to create systems that are reliable, interpretable and domain-aware. These innovations will open the door to trustworthy AI applications in medicine, science, food information engineering, geodata and education.
Objective
Artificial Intelligence (AI) is transforming research, industry, and society, with Large Language Models (LLMs) playing a central role. While LLMs excel in natural language understanding, reasoning, and content generation, they also exhibit hallucinations, security vulnerabilities, ethical concerns, and regulatory issues. These challenges are particularly critical in healthcare and education, where accuracy, reliability, and fairness are essential. Addressing these shortcomings requires AI paradigms that enhance interpretability, robustness, and compliance.
THIRDWAVE aims to establish an international, interdisciplinary network to advance LLM-driven neuro-symbolic AI, integrating symbolic AI with LLMs to create interpretable, reliable, and domain-aware systems. This approach enables AI to leverage structured knowledge, improve decision-making, and comply with domain-specific constraints, making it more applicable to real-world challenges.
The project is structured around four key objectives: O1) Understanding LLMs: Analyzing capabilities and limitations to improve performance, usability, and trustworthiness. O2) Enhancing LLMs: Improving fairness, factual accuracy, and robustness through external knowledge sources and human collaboration. O3) Advancing LLM-driven Neuro-Symbolic AI: Developing hybrid systems that combine LLMs with symbolic reasoning for structured knowledge representation and better decision support. O4) Use Cases & Evaluation: Applying LLM-driven neuro-symbolic AI in healthcare, education, geodata, and food information engineering, validating scalability and societal impact.
By fostering collaboration among AI researchers, domain experts, and industry partners, THIRDWAVE will bridge the gap between data-driven and knowledge-driven AI, ensuring LLMs become interpretable, ethically aligned, and domain-aware. The project’s findings will inform AI regulation, advance research, and drive innovation, contributing to responsible AI development.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- engineering and technology electrical engineering, electronic engineering, information engineering information engineering
- natural sciences computer and information sciences knowledge engineering
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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(opens in new window) HORIZON-MSCA-2024-SE-01
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30167 Hannover
Germany
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Participants (9)
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LS1 3HB Leeds
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28040 Madrid
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00185 Roma
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00184 Roma
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105 61 ATHINA
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153 43 ATHINA
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28036 MADRID
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MSD 2080 MSIDA
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30167 Hannover
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Partners (8)
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721302 Kharagpur
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47402 Bloomington
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16802-7000 UNIVERSITY PARK PA
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28046 MADRID
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23955 6900 Thuwal
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HANOI
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7701 Rondebosch
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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0000000 YAOUNDE
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