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New Bengali Geometry Benchmark Tests VLM Modality Reliance

研究人员推出了 ChitraMiti-12.8k,这是一个新的基准,旨在评估视觉语言模型 (VLM) 在孟加拉语几何推理中的视觉基础和模态依赖性。该基准包括合成几何问题和来自学校教科书的补充图。对几个 VLM 的评估显示,虽然结构化描述可以作为视觉输入的代理,但模型在跨模态验证方面存在困难,并且即使在正确回答的情况下,也容易被文本不准确之处误导。在 ChitraMiti-12.8k 上进行微调显示出改进,但与最强的零样本模型相比,仍然存在显著的性能差距。 AI

影响 该基准可以推动低资源语言的多模态推理评估,推动 VLM 开发朝着更鲁棒的跨模态验证方向发展。

排序理由 该集群包含一篇介绍新 AI 模型评估基准的学术论文。

在 arXiv cs.CV 阅读 →

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New Bengali Geometry Benchmark Tests VLM Modality Reliance

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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Khan Raiyan Ibne Reza, Sanjana Aktar Maria, Sumaiya Tabassum Nimi, Md Adnan Arefeen ·

    ChitraMiti:在孟加拉语几何推理中进行视觉基础和模态依赖性基准测试

    arXiv:2609.12509v1 Announce Type: new Abstract: Evaluation of vision-language models (VLMs) for multimodal mathematical reasoning remains limited for low-resource languages and for geometry problems that require reading a diagram and a question together. We introduce ChitraMiti-1…