Project
PaA-7
Integration of Logical Tensor Networks into LLMs for Explainable and Efficient Reasoning
Project Heads
Martin Eigel, Alex Goeßmann, Sven Wang
Project Members
Janina Schütte
Project Duration
01.09.2025 − 31.08.2027
Located at
WIAS
Description
Despite human-like chains of thought in reasoning language models, generated reasoning steps merely rely on trained next token probabilities. To strengthen explainability and efficiency, we capture specific problem structures by logic tensor networks for rigorous deduction in a hybrid LLM reasoning method.
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