On the (In)effectiveness of AMR Augmentation for Large Language Models

Paper recorded by Signals 4 on 2026-09-30 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-30 on arXiv · recorded by Signals 4 on 2026-10-01

Category: cs.CL · 自然语言处理 · first seen 2026-10-01

Abstract

While Abstract Meaning Representation (AMR) has historically improved performance on a range of NLP tasks, the benefit---or lack thereof---of AMR augmentation for modern LLMs is thus far unclear. In this paper, we attempt to reproduce recent work that reported substantial downstream gains from AMR augmentation, finding that these are likely due to specific choices in the experimental settings used

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