| --- |
| dataset_info: |
| features: |
| - name: images |
| sequence: image |
| - name: question |
| dtype: string |
| - name: label |
| dtype: string |
| - name: task |
| dtype: string |
| - name: num_images |
| dtype: int64 |
| - name: image_names |
| sequence: string |
| - name: injected |
| dtype: bool |
| - name: object_counts |
| dtype: string |
| configs: |
| - config_name: count |
| data_files: |
| - split: train |
| path: data/count.parquet |
| - config_name: existence_adversarial |
| data_files: |
| - split: train |
| path: data/existence_adversarial.parquet |
| - config_name: existence_popular |
| data_files: |
| - split: train |
| path: data/existence_popular.parquet |
| - config_name: existence_random |
| data_files: |
| - split: train |
| path: data/existence_random.parquet |
| license: cc-by-4.0 |
| task_categories: |
| - visual-question-answering |
| language: |
| - en |
| tags: |
| - multi-image |
| - hallucination |
| - benchmark |
| - vision-language-model |
| - multimodal |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # MIHBench |
|
|
| Multi-Image Hallucination Benchmark for evaluating multi-image understanding in MLLMs. 3,200 samples across 4 tasks (800 each), with each sample containing 2-4 images from COCO. |
|
|
| ## Fields |
|
|
| | Field | Description | |
| |-------|-------------| |
| | images | 2-4 images (list) | |
| | question | Natural language question about the images | |
| | label | Ground truth: "yes" or "no" | |
| | task | Task identifier | |
| | num_images | Number of images in the sample | |
| | image_names | Source image filenames | |
|
|
| Additional fields for **count** task: `injected` (bool), `object_counts` (JSON string). |
|
|
| ## Tasks |
|
|
| | Task | # Images | Description | |
| |------|----------|-------------| |
| | count | 2 | Same number of target object in both images? | |
| | existence_adversarial | 3 | Target object exists in all images? (rare/confusing objects) | |
| | existence_popular | 3 | Target object exists in all images? (common objects) | |
| | existence_random | 3 | Target object exists in all images? (random objects) | |
| |
| ## Evaluation |
| |
| ``` |
| metrics: Accuracy, Precision, Recall, F1 |
| parser: yes/no binary |
| ``` |
| |
| ## Source |
| |
| Original data from [MIHBench](https://arxiv.org/abs/2505.xxxxx) (ACM Multimedia 2025). |
| |
