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A Logic-Grounded Language Model Paradigm For Relational Data

CORDIS · observation · Publication date unknown

A Logic-Grounded Language Model Paradigm For Relational Data "Relational databases power finance, healthcare and science, yet they are not natively understood by today’s Large Language Models (LLMs). LLMs lack relational understanding: they are trained on text and, to consume tables in a prompt, they must convert them into a sequence of words, destroying the connections and rules - such as joins, keys and constraints - that carry logic in relational data. Scaling monolithic models is not the answer: it dilutes relational structure, demands prohibitive energy, and forces organizations to expose sensitive data to external clouds. The GENESIS project confronts this challenge by establishing a formal theory of Relational Grounding, a new paradigm that defines how relational logic can be intrinsically represented in language models. This theory underpins our approach of Grounded Self-Supervision. Instead of retrofitting LLMs for relational data, our framework uses an organization's database - schema, constraints, and content - as a blueprint to automatically

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recordType

award

status

SIGNED

region

EU

value

2488880

unit

EUR