ImageMining: A Benchmark for Multimodal Model Evaluation

217 examples across 7 top-level categories and 23 subcategories comprise this benchmark for evaluating multimodal models. Created by zai-org, the dataset requires models to identify entities and perform multi-step reasoning with search-augmented information to answer complex questions. It was last updated on 2026-05-16.

Use Cases

• Benchmarking entity identification capabilities based on image content
• Evaluating multi-step reasoning performance in multimodal models
• Testing model ability to answer complex questions that go beyond simple visual understanding

Strengths

• 217 examples provide a defined test set
• Structured into 7 top-level categories and 23 subcategories for targeted evaluation

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download

Provenance

Source

huggingface

Freshness

Last updated 2026-05-16 09:27:46