| --- |
| license: cc-by-4.0 |
| task_categories: |
| - visual-question-answering |
| tags: |
| - vlm |
| - robustness |
| - answer-flip |
| - benchmark |
| pretty_name: FlipDir Answer-Flip Testbeds |
| --- |
| |
| # FlipDir — Answer-Flip Testbeds under Benign Visual Variations |
|
|
| Model-conditioned testbeds of **answer flips**: cases where a vision–language model |
| changes its final answer under a benign visual variation (exposure, white balance, |
| JPEG, blur, small rotation) that a human would treat as inconsequential. Companion |
| data for the FlipDir defense — code at **https://github.com/YeonsungJung/FlipDir**. |
|
|
| ## What is (and isn't) here |
|
|
| Each testbed ships the **metadata + seeds + variation parameters + flip labels**, not |
| the rendered images. Because generation is deterministic (batch-1 greedy, fixed seed |
| chain), the varied images regenerate **byte-for-byte** from the original source image + |
| the stored seed/params using the released code. This keeps the release small and avoids |
| redistributing the source datasets' images. |
|
|
| Regenerate images: |
| ```bash |
| # in the code repo, with the same seed |
| bash run_ours.sh <qwen8b|gemma12b> <attack> gen |
| ``` |
|
|
| ## Layout |
|
|
| ``` |
| paper/<model>/<testbed>/<split>/meta/*.json # settings used in the paper |
| etc/<model>/<testbed>/<split>/meta/*.json # extra intensity/seed variants |
| <model> = qwen3vl-8b | gemma-3-12b |
| <testbed> = exposure_shift | wb_shift | jpeg_double (M3CoT, science) |
| exposure_shift_robo | brightness_shift_robo | motion_shake_robo (Robo2VLM) |
| window_level | medical_blur | detector_rotation (GMAI-MMBench, medical) |
| <split> = train | test |
| ``` |
|
|
| A flip label is defined relative to the model's own clean-image answer, so every testbed |
| is built **per model**. Current release: Gemma-3-12B all 9 testbeds; Qwen3-VL-8B 7 of 9 |
| (robotics `exposure_shift_robo` / `brightness_shift_robo` are being regenerated). |
|
|
| ## Metadata schema (per parent question) |
|
|
| `id, split, category_rank, attack, text_attack, image_attack_intensity, model, seed, gt, |
| prompt, orig_img_path, orig_raw, orig_norm, orig_correct, raw_counts, flips, nonflips, |
| limits, gen_cfg` — `orig_norm` is the clean-image answer, `flips`/`nonflips` list the |
| varied children and their (raw, normalized) outputs, `seed`+`image_attack_intensity` |
| reproduce the variation, `orig_img_path` points into the source dataset. |
|
|
| ## Source datasets (obtain images from the originals) |
|
|
| - **M3CoT** — science reasoning · https://huggingface.co/datasets/LightChen2333/M3CoT |
| - **Robo2VLM** — robot-scene VQA · https://huggingface.co/datasets/keplerc/Robo2VLM |
| - **GMAI-MMBench** — medical VQA · https://huggingface.co/datasets/OpenGVLab/GMAI-MMBench |
|
|
| Please follow each source dataset's license for the underlying images. |
|
|
| ## Citation |
|
|
| FlipDir (preprint). Code and paper: https://github.com/YeonsungJung/FlipDir |
|
|
