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When Does Meaning Backfire? Investigating the Role of AMRs in NLI
Junghyun Min, Xiulin Yang, Shira Wein
https://arxiv.org/abs/2506.14613 https://

When Does Meaning Backfire? Investigating the Role of AMRs in NLI
Natural Language Inference (NLI) relies heavily on adequately parsing the semantic content of the premise and hypothesis. In this work, we investigate whether adding semantic information in the form of an Abstract Meaning Representation (AMR) helps pretrained language models better generalize in NLI. Our experiments integrating AMR into NLI in both fine-tuning and prompting settings show that the presence of AMR in fine-tuning hinders model generalization while prompting with AMR leads to sligh…