Meta4XNLI：用于隐喻检测与解释的跨语言平行语料库
Meta4XNLI: A Crosslingual Parallel Corpus for Metaphor Detection and Interpretation
AI总结：
本文提出首个面向隐喻检测与解释的英西平行NLI数据集Meta4XNLI，发现微调编码器在隐喻检测上优于仅解码器LLM，并揭示翻译对隐喻跨语言保留与模型性能的影响。
摘要：
隐喻在日常语言中无处不在，却常常被忽视。作为一种复杂的认知—语言现象，隐喻为评估语言模型能否捕捉更深层的意义（包括语义、语用和文化语境）提供了有价值的手段。在本工作中，我们提出了 Meta4XNLI，这是首个为自然语言推理（NLI）新标注的平行数据集，同时覆盖英语和西班牙语的隐喻检测与解释任务。Meta4XNLI 有助于在多语言和跨语言场景下比较基于编码器和基于解码器的模型在检测与理解隐喻语言方面的能力。我们的结果表明，在隐喻检测任务上，经过微调的编码器模型优于仅解码器的大语言模型（LLMs）。隐喻解释通过 NLI 框架进行评估，掩码语言模型与自回归模型表现相当，但当推理受到隐喻语言影响时，性能会明显下降。我们的研究还发现，翻译在隐喻跨语言保留或丢失中起着重要作用，其引入的偏移可能影响隐喻的出现频率和模型性能。这些发现凸显了像 Meta4XNLI 这样的资源对于推进语言模型能力分析以及加深我们对跨语言隐喻处理理解的重要性。此外，该数据集为研究隐喻解释、跨语言隐喻可迁移性以及翻译对多语言标注资源建设的影响提供了此前无法获得的机会。
英文摘要：
Metaphors are a ubiquitous but often overlooked part of everyday language. As a complex cognitive-linguistic phenomenon, they provide a valuable means to evaluate whether language models can capture deeper aspects of meaning, including semantic, pragmatic, and cultural context. In this work, we present Meta4XNLI, the first parallel dataset for Natural Language Inference (NLI) newly annotated for metaphor detection and interpretation in both English and Spanish. Meta4XNLI facilitates the comparison of encoder- and decoder-based models in detecting and understanding metaphorical language in multilingual and cross-lingual settings. Our results show that fine-tuned encoders outperform decoders-only LLMs in metaphor detection. Metaphor interpretation is evaluated via the NLI framework with comparable performance of masked and autoregressive models, which notably decreases when the inference is affected by metaphorical language. Our study also finds that translation plays an important role in the preservation or loss of metaphors across languages, introducing shifts that might impact metaphor occurrence and model performance. These findings underscore the importance of resources like Meta4XNLI for advancing the analysis of the capabilities of language models and improving our understanding of metaphor processing across languages. Furthermore, the dataset offers previously unavailable opportunities to investigate metaphor interpretation, cross-lingual metaphor transferability, and the impact of translation on the development of multilingual annotated resources.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
