id int64 | category string | description string | why_hard string | image image | candidate_labels list | expected_label string | model_winner string | model_scores_json string | is_correct bool | model_name string | error_type string |
|---|---|---|---|---|---|---|---|---|---|---|---|
1 | counting | Image has exactly 7 red circles. Does model know the count? | Vision models notoriously struggle with counting beyond ~4 objects | [
"seven red circles",
"five red circles",
"three red circles"
] | seven red circles | seven red circles | {"seven red circles": 0.99755859375, "five red circles": 0.97607421875, "three red circles": 0.48046875} | true | google/siglip2-base-patch16-224 | none | |
2 | spatial_relations | Orange square is on top of blue circle. Tests preposition binding. | Contrastive models often ignore relational structure; both labels share the same nouns | [
"an orange square on top of a blue circle",
"a blue circle on top of an orange square"
] | an orange square on top of a blue circle | an orange square on top of a blue circle | {"an orange square on top of a blue circle": 1.0, "a blue circle on top of an orange square": 1.0} | true | google/siglip2-base-patch16-224 | none | |
3 | negation | Empty white plate. Tests whether model understands 'no food'. | CLIP-style models are known to largely ignore negation in text | [
"a plate with no food on it",
"a plate with food on it"
] | a plate with no food on it | a plate with no food on it | {"a plate with no food on it": 0.05224609375, "a plate with food on it": 0.002132415771484375} | true | google/siglip2-base-patch16-224 | none | |
4 | orientation | Triangle pointing downward (upside-down). Tests orientation awareness. | Orientation is a subtle visual feature often ignored in web-crawled training data | [
"an upside-down triangle",
"a triangle pointing up"
] | an upside-down triangle | a triangle pointing up | {"an upside-down triangle": 0.81298828125, "a triangle pointing up": 0.94482421875} | false | google/siglip2-base-patch16-224 | orientation | |
5 | color_identification | Teal/cyan rectangle on dark background. Tests precise color naming. | Boundary colors like teal (between blue and green) challenge color-text alignment | [
"a teal rectangle",
"a green rectangle",
"a blue rectangle"
] | a teal rectangle | a teal rectangle | {"a teal rectangle": 0.99755859375, "a green rectangle": 0.97900390625, "a blue rectangle": 0.93701171875} | true | google/siglip2-base-patch16-224 | none | |
6 | size_comparison | One large circle and one small circle. Tests relative size reasoning. | Relative size requires comparing objects within the scene, not just recognizing them | [
"a large circle and a small circle",
"two circles of the same size"
] | a large circle and a small circle | a large circle and a small circle | {"a large circle and a small circle": 0.99072265625, "two circles of the same size": 0.98095703125} | true | google/siglip2-base-patch16-224 | none | |
7 | text_in_image | Image showing the word EXIT. Tests OCR-level vision-language binding. | Base vision-language models aren't trained for OCR; text reading is unreliable | [
"a sign that says EXIT",
"a sign that says ENTER",
"a sign that says STOP"
] | a sign that says EXIT | a sign that says EXIT | {"a sign that says EXIT": 0.0035648345947265625, "a sign that says ENTER": 0.0032482147216796875, "a sign that says STOP": 0.00257110595703125} | true | google/siglip2-base-patch16-224 | none | |
8 | shape_finegrain | A wide ellipse (clearly not a circle). Tests fine-grained shape discrimination. | Circle and ellipse are visually similar; both are 'oval' shapes in natural language | [
"a red ellipse",
"a red circle"
] | a red ellipse | a red ellipse | {"a red ellipse": 0.9970703125, "a red circle": 0.79833984375} | true | google/siglip2-base-patch16-224 | none | |
9 | composition_vs_components | Three circles arranged in a triangle pattern. Part vs. whole. | Requires understanding both components AND their spatial arrangement as a gestalt | [
"three circles arranged in a triangle",
"a triangle",
"three separate circles"
] | three circles arranged in a triangle | three circles arranged in a triangle | {"three circles arranged in a triangle": 0.99072265625, "a triangle": 0.021942138671875, "three separate circles": 0.880859375} | true | google/siglip2-base-patch16-224 | none | |
10 | quantity_fullness | Container ~85% full of blue liquid. Tests quantity/fullness language. | Quantitative fullness requires calibrated visual-language grounding | [
"a nearly full container",
"a half-empty container",
"an empty container"
] | a nearly full container | a half-empty container | {"a nearly full container": 0.0017271041870117188, "a half-empty container": 0.0299835205078125, "an empty container": 0.010986328125} | false | google/siglip2-base-patch16-224 | quantity_fullness |
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