Author

N. Saccomanno

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#natural language process... Review Oct 2026

Natural Language to First-Order Logic LLM-based Autoformalization

This paper provides a principled definition for the FOL-autoformalization task by distinguishing Ontology Extraction from Logical Translation and identifies open challenges in benchmarking, semantic evaluation, ontology-aware methods, and end-to-end applications.

Andrea Brunello, Cristian Curaba, Luca Geatti et al. · 1 citation

#artificial intelligence Review Jun 2026

Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling

An LLM-based framework to support humans in manual reviewing NL-to-FOL datasets is proposed, and it is empirically show that it is possible to achieve 90% dataset accuracy after reviewing fewer than 20% of instances, compared to over 76% required by unguided review.

Andrea Brunello, Cristian Curaba, Luca Geatti et al. · arXiv.org · 2 citations