When Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Logical Structure
Large language models (LLMs) have achieved strong performance across diverse reasoning tasks, yet it remains unclear whether this performance reflects an understanding of underlying logical structure or a reliance on shallow semantic cues. A key indicator of such understanding is whether models treat logically equivalent inputs consistently, producing the same predictions despite differences in expression. Through systematic evaluation on curated data, we show that even strong LLMs often fail this test: they do not consistently preserve predictions across logically equivalent inputs and generalize poorly to unseen logical forms. To address this limitation, we propose LoGIcal STructure-gui...
| Authors | Xuyuan Liu, Xinshuai Dong, Elynn Chen et al. |
|---|---|
| Primary category | cs.AI |
| Published | 18 October 2026 |
| Last updated at source | 21 October 2026 |
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