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BLINDSPOT
8 of 9 frontier models score nearly the same on a biology diagram benchmark when the image is completely removed. This is a 10-row sample of the scored responses. Access is auto-approved — fill in your details to view the data.
Full dataset (6,335 responses · 9 models · 4 conditions · 181 items): Nalandadata/BLINDSPOT — requires access request.
The BLINDSPOT benchmark shows an unlabelled scientific diagram to a model and asks it to name every part a leader line points to. The labeled original is the answer key. The control condition removes the image entirely — models only receive the subject name. The finding: most models are reciting from training data, not reading the diagram.
Key finding
grounded contribution = told_score − no_image_score (percentage points)
recitation share = no_image_score ÷ told_score (%)
gpt-4o-mini recitation share: 99% (+0.2 pts grounded, CI contains zero — the image contributes nothing).
gpt-5.6-luna recitation share: 9% (+46.2 pts grounded — highest genuine visual contribution).
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 in the release?
All 181 items come from copyrighted textbooks and a proprietary question bank. Only scores and predicted names are released publicly.
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