bufo-bench / README.md
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bufo-bench v1: 5 tasks, froge-original ref, 15 judged evals with expert labels
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metadata
license: other
license_name: unknown-community-meme-benchmark-use-only
task_categories:
  - text-to-image
  - image-to-image
tags:
  - benchmark
  - image-generation-evaluation
  - vision-language-judge
  - frog
  - meme
  - bufo
pretty_name: bufo-bench
configs:
  - config_name: default
    data_files:
      - split: tasks
        path: data/tasks.jsonl
      - split: evaluations
        path: data/evaluations.jsonl

🐸 bufo-bench

Can your image model draw a real bufo β€” or does it draw a generic cute frog and call it a day?

Bufo is a riff on the original "worry frog" / froge meme: simplex smooth construction, fresh leaf-green, LARGE pale-yellow eyes with huge near-black pupils in a worried averted gaze, and an iconic little nose (protruding snout, tiny nostrils, no mouth). Image models reliably fail at this β€” they draw bright-green tree-frogs with stalk eyes and big smiles instead.

What's here

  • data/tasks.jsonl (5 rows) β€” the eval set. Each row: task_id, title, prompt (task instruction), checks (verifiable checklist), style_block (shared bufo spec prepended to every generation prompt), reference_images, notes. Run a model on all five with the style_block + references, then judge.
  • references/froge-original.png β€” ground truth: the original worry-frog (via KYM photo #2561104).
  • references/negative-*.png β€” documented off-model riffs (what "close but wrong" looks like: olive-drab, deadpan, MS-paint).
  • data/evaluations.jsonl (15 rows + evaluations/<run>/<task>.png) β€” every judged output so far: model, provider, track, per-axis scores (shape/color/face/style, 0–2 each), bufoness (0–8), task_score, judge verdict, judge model, rubric version, and expert_verdict where a human expert graded it (null = judge only).

Scoring (see the bench repo for the full rubric)

bufoness = shape + color + face + style. PASS iff bufoness β‰₯ 6 AND all task checks hold AND no axis is 0. Model score = pass rate over the 5 tasks. The load-bearing discriminator is the gaze test: a frog that looks AT you is not worried β€” worry means averted, half-lidded, or closed eyes with no mouth.

Provenance & license

Reference art is community meme culture of unclear authorship (see SOURCES in the bench repo); model outputs belong to whoever generated them. Provided for benchmark/evaluation use. If you hold rights to the original froge and want it handled differently, open an issue on the bench repo.

Bench code, runner, judge prompts, and eval queue: local bufo-bench project (being open-sourced separately).