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New Bengali Geometry Benchmark Tests VLM Modality Reliance

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced ChitraMiti-12.8k, a new benchmark designed to evaluate visual grounding and modality reliance in Bengali geometric reasoning for vision-language models (VLMs). The benchmark includes synthetic geometry problems and complementary diagrams from school textbooks. Evaluations across several VLMs revealed that while structured descriptions can serve as a proxy for visual input, models struggle with cross-modal verification and are easily misled by textual inaccuracies, even when answering correctly. Fine-tuning on ChitraMiti-12.8k shows improvement, but a significant performance gap persists compared to the strongest zero-shot models. AI

IMPACT This benchmark could advance the evaluation of multimodal reasoning in low-resource languages, pushing VLM development towards more robust cross-modal verification.

RANK_REASON The cluster contains an academic paper introducing a new benchmark for evaluating AI models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Bengali Geometry Benchmark Tests VLM Modality Reliance

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The cluster contains an academic paper introducing a new benchmark for evaluating AI models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

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

    ChitraMiti: Benchmarking Visual Grounding and Modality Reliance in Bengali Geometric Reasoning

    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…

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