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多模态学习情境下词汇推断研究
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本文探讨了在多模态学习情境下,学习者如何推断句子中描述配对图像的陌生词汇意义。通过不同图像-文本对的研究,分析了数据特征对推断陌生词汇的影响,以及参与者的语言背景与成功率的关联。研究发现,仅某些直观特征与参与者表现高度相关,并指出需进一步研究预测成功的关键特征。同时,分析了AI系统对参与者表现的推理能力,为未来改进推理能力提供了方向。

arXiv:2510.09815v1 Announce Type: cross Abstract: We investigate a new setting for foreign language learning, where learners infer the meaning of unfamiliar words in a multimodal context of a sentence describing a paired image. We conduct studies with human participants using different image-text pairs. We analyze the features of the data (i.e., images and texts) that make it easier for participants to infer the meaning of a masked or unfamiliar word, and what language backgrounds of the participants correlate with success. We find only some intuitive features have strong correlations with participant performance, prompting the need for further investigating of predictive features for success in these tasks. We also analyze the ability of AI systems to reason about participant performance, and discover promising future directions for improving this reasoning ability.

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多模态学习 词汇推断 AI推理 语言学习 图像-文本对
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