Natural Language to First-Order Logic LLM-based Autoformalization

arXiv:2610.12030 · cs.CL · Submitted 2026-10-08 · Read on arXiv

cs.CL

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Ontology — 25× in this paper · explained in 2 episodes
• Verification — 25× in this paper · explained in 2 episodes
• Natural Language — 23× in this paper
• Fine-Tuning — 10× in this paper · explained in 5 episodes
• First-Order Logic — 10× in this paper
• Benchmark — 5× in this paper · explained in 2 episodes
• Axioms — 4× in this paper · explained in 2 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Formal Verification — 4× in this paper · explained in 2 episodes
• SMT solver — 4× in this paper · explained in 2 episodes
• Alignment — 3× in this paper · explained in 1 episode
• Grounding — 3× in this paper · explained in 3 episodes
• RAG — 3× in this paper · explained in 3 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Annotation Errors — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Grade Grinder Corpus — 2× in this paper
• LLM judge — 2× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Logical Translation — 2× in this paper
• Ontology Extraction — 2× in this paper
• Satisfiability Modulo Theories — 2× in this paper
• Self-consistency — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Feature Extraction — 1× in this paper · explained in 2 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• In-Context Learning (ICL) — 1× in this paper · explained in 5 episodes
• Natural Language Inference — 1× in this paper
• Natural Language Inference (NLI) — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Supervised Fine-tuning — 1× in this paper
• Text-to-SQL — 1× in this paper · explained in 3 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling
• VERUS-LM: a Versatile Framework for Combining LLMs with Symbolic Reasoning
• Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systems
• A Short Review for Ontology Learning: Stride to Large Language Models Trend
• Formal Specifications from Natural Language
• A Survey on Semantic Parsing
• $\forall$uto$\exists$val: Autonomous Assessment of LLMs in Formal Synthesis and Interpretation Tasks
• LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations
• Autoformalizing Natural Language to First-Order Logic: A Case Study in Logical Fallacy Detection
• LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning
• From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems
• Enhancing Reasoning Capabilities of LLMs via Principled Synthetic Logic Corpus
• LOGicalThought: Logic-Based Ontological Grounding of LLMs for High-Assurance Reasoning
• Strategies for Improving NL-to-FOL Translation with LLMs: Data Generation, Incremental Fine-Tuning, and Verification
• LOGICPO: Efficient Translation of NL-based Logical Problems to FOL using LLMs and Preference Optimization
• Advancing Natural Language Formalization to First Order Logic with Fine-tuned LLMs
• AR-LSAT: Investigating Analytical Reasoning of Text

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