LTLGuard: Formalizing LTL Specifications with Compact Language Models and Lightweight Symbolic Reasoning
On the map: LLM reasoning → Reasoning for agents, planning and code
Abstract (arXiv)
Translating informal requirements into formal specifications is challenging due to the ambiguity and variability of natural language (NL). This challenge is particularly pronounced when relying on compact (small and medium) language models, which may lack robust knowledge of temporal logic and thus struggle to produce syntactically valid and consistent formal specifications. In this work, we focus on enabling resource-efficient open-weight models (4B--14B parameters) to generate correct linear temporal logic (LTL) specifications from informal requirements. We present LTLGuard, a modular toolchain that combines constrained generation with formal consistency checking to generate conflict-free LTL specifications from informal input. Our method integrates the generative capabilities of model languages with lightweight automated reasoning tools to iteratively refine candidate specifications, understand the origin of the conflicts and thus help in eliminating inconsistencies. We demonstrate the usability and the effectiveness of our approach and perform quantitative evaluation of the resulting framework.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Reasoning for agents, planning and code, one of 17 directions in LLM reasoning. Builds on 9 of its 26 references that are in the map. First posted on arXiv 5 Mar 2026.
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9 of 26 references.
References · 9
- 2020Language Models are Few-Shot Learnerscited by 32,419
- 2024Hallucination of Multimodal Large Language Models: A Surveycited by 388
- 2024SynCode: LLM Generation with Grammar Augmentationcited by 69
- 2023nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Modelscited by 60
- 2022Formal Specifications from Natural Languagecited by 33
- 2021DeepSTL -- From English Requirements to Signal Temporal Logiccited by 22
- 2025Bridging Natural Language and Formal Specification--Automated Translation of Software Requirements to LTL via Hierarchical Semantics Decomposition Using LLMscited by 9
- 2014Formal Consistency Checking over Specifications in Natural Languagescited by 8
- 2025How Much Do LLMs Hallucinate across Languages? On Realistic Multilingual Estimation of LLM Hallucinationcited by 5
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- 2026Automatic Translation of Unstructured Requirements into Linear Temporal Logic through Large Language Models ↗
- 2026Infinite Trace Objectives with Finite Trace Techniques: Translating LTL to LTLf+
- 2024LTLBench: Towards Benchmarks for Evaluating Temporal Reasoning in Large Language Models
- 2026ReasonSTL: Bridging Natural Language and Signal Temporal Logic via Tool-Augmented Process-Rewarded Learning
- 2026Formalizing and validating properties in Asmeta with Large Language Models (Extended Abstract) ↗
- 2026ToolGate: Contract-Grounded and Verified Tool Execution for LLMs
- 2026Pushing the Boundaries of Natural Reasoning: Interleaved Bonus from Formal-Logic Verification
- 2026RTL-BenchLS: A Large-Scale Benchmark for RTL Reasoning and Generation with Large Language Models