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Beyond Surface Forms: Symbolic Edits as a Test for Logical Reasoning with LLMs

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Logical reasoning with large language models (LLMs) is a critical capability, as it reflects a system's ability to correctly deduce hypotheses from a given context using faithful deductive processes. However, LLM reasoning has often been shown to be sensitive to small surface-level variations in problem formulation, raising questions about whether models truly follow the underlying logical structure. Studying this behavior is challenging because the symbolic components of logical problems, such as operators and predicates, are difficult to systematically manipulate in natural language. We intr

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