Text-JEPA: A Joint Embedding Predictive Architecture for the Conversion of Natural Language into First-Order Logic

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Trong Le, Phat Thai, Sang Nguyen, Minh Hua, Ngan Pham, Thang Bui, Tho Quan, Tuan Bui

Published: 01 Jan 2026, Last Modified: 15 Mar 2026CrossrefEveryoneRevisionsCC BY-SA 4.0
Abstract: The conversion of knowledge from natural language (NL) into first-order logic (FOL) plays a crucial role in Knowledge Representation and Cognitive Science, particularly in the context of hybrid Neural-Symbolic models. This process not only facilitates logical knowledge modeling but also enhances the effectiveness of language models and symbolic reasoning systems. The binary nature of FOL—where statements are either true or false—ensures greater consistency and efficiency in these models.