---
license: cc-by-4.0
task_categories:
- visual-question-answering
language:
- en
tags:
- benchmark
- biology
- diagram-understanding
- vision-language
- no-image-control
- sample
size_categories:
- n<20
dataset_info:
  features:
  - name: item_id
    dtype: string
  - name: model
    dtype: string
  - name: condition
    dtype: string
  - name: f1
    dtype: float64
  - name: precision
    dtype: float64
  - name: recall
    dtype: float64
  - name: n_pred
    dtype: int64
  - name: n_key
    dtype: int64
  - name: predicted_names
    list: string
  - name: key_names
    list: string
  - name: subject
    dtype: string
  - name: tier
    dtype: string
  - name: unsolved_core
    dtype: bool
  - name: recitable
    dtype: bool
  - name: parse_ok
    dtype: bool
  - name: unlabeled_image
    dtype: image
  - name: labeled_image
    dtype: image
  splits:
  - name: train
    num_bytes: 5287793
    num_examples: 10
  download_size: 5295647
  dataset_size: 5287793
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# BLINDSPOT — Public Sample (10 rows)

**10 representative rows from [Nalandadata/BLINDSPOT](https://huggingface.co/datasets/Nalandadata/BLINDSPOT) — no login required.**

A model is shown an unlabelled scientific diagram and must name every part a leader line points to. This sample shows scored responses from the benchmark's `results.jsonl` file across different models and conditions.

> **Full dataset (6,335 scored responses, 9 models, 4 conditions, 181 items):** [Nalandadata/BLINDSPOT](https://huggingface.co/datasets/Nalandadata/BLINDSPOT) — requires access request.

---

## Key finding

The headline result is not the leaderboard — it is the **no-image control**. When the picture is removed and models are only told the subject name, 8 of 9 models keep 70–100% of their score. For `gpt-4o-mini`, the image contributes nothing (+0.2 pts, CI contains zero).

```
grounded contribution = told − no-image   (percentage points)
recitation share      = no-image ÷ told   (%)
```

## Columns

| Column | Type | Description |
|---|---|---|
| `item_id` | string | Public item code (`NALANDA-N`) |
| `model` | string | Model identifier, e.g. `google/gemini-3.6-flash` |
| `condition` | string | `blind`, `told`, `desc`, or `no-image` |
| `f1` | float | Synonym-aware name-set F1 (0–1) |
| `precision` | float | Precision component |
| `recall` | float | Recall component |
| `n_pred` | int | Number of names the model predicted |
| `n_key` | int | Number of ground-truth names |
| `predicted_names` | list[str] | The model's label list |
| `key_names` | list[str] | Ground-truth anatomical names |
| `subject` | string | Short factual description of the diagram |
| `tier` | string | Item tier (`core` or `extended`) |
| `unsolved_core` | bool | True if no baseline model solved this item |
| `recitable` | bool | True if ≥1 model scored F1 ≥ 0.5 with no image |
| `parse_ok` | bool | Whether the model's output parsed correctly |

## Why no images?

All 181 benchmark items come from copyrighted textbooks and a proprietary question bank. Only scores and predicted names are released; source figures are not distributable.

---

For enquiries: [info@nalandadata.ai](mailto:info@nalandadata.ai) · [nalandadata.ai](https://nalandadata.ai)