MathCoder-VL is a series of open-source large multimodal models tailored for general math problem-solving. The dataset likely contains multimodal math problems combining visual and textual elements. It was created by MathLLMs and last updated on October 11, 2025.
Use Cases
- Train multimodal models for math problem-solving based on the described combination of vision and code.
- Benchmark visual question answering performance on geometry diagrams and synthetic scenes.
- Evaluate reasoning capabilities on math word problems and textbook QA.
- Develop image-to-code models for mathematical figures based on the FigCodifier-8B model mentioned.
- Fine-tune models for multi-modal QA tasks involving mathematics.
Strengths
- Dataset is associated with a published paper (arXiv:2505.10557).
- Dataset is linked to a GitHub repository (https://github.com/mathllm/MathCoder).
- Dataset was last updated on October 11, 2025.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Column-level documentation is absent; field semantics must be inferred after download.
- Row count is unknown, which may limit suitability assessment.
Provenance
- Source
- MathLLMs
- Freshness
- Last updated 2025-10-11 05:14:13; freshness should be verified.