| --- |
| license: cc-by-4.0 |
| tags: |
| - vision-language |
| - llm-as-judge |
| - evaluation |
| - causal-inference |
| - multimodal |
| --- |
| |
| # GroundJudge: constructed artifacts and judge verdicts |
|
|
| Supporting data for **"Do Vision-Language Judges Use the Image? A Causal |
| Audit of Visual Grounding in Multimodal Evaluation"** (ICLR 2027 |
| submission). Code: see the paper's GitHub repository. |
|
|
| This repo contains **only this project's own constructed/generated |
| artifacts** — every image variant, injected trace, and per-instance judge |
| verdict behind the paper's tables. It deliberately does **not** include: |
|
|
| - Raw source datasets (GQA, ChartQA, MathVista, ScienceQA, HallusionBench, |
| VL-RewardBench) — these are public; download them from their original |
| sources (see the paper's Appendix C and the `groundjudge/src/data/` |
| ingestion scripts in the code repo for exact URLs/HF dataset IDs). |
| - Judge model weights (Qwen2.5-VL, InternVL3, LLaVA-OneVision, |
| Llama-3.2-Vision, VisualPRM, SDXL-inpainting, SAM2) — these are public |
| checkpoints on the Hugging Face Hub; load them directly via |
| `transformers`/`diffusers` as the code does. |
|
|
| ## Contents |
|
|
| ``` |
| images/<dataset>/<instance_id>/ |
| x.png # original image |
| x_plus.png # content-preserving re-encoding (control) |
| x_blank.png # blanked image (ablation) |
| x_mismatch.png # mismatched image from a different instance (ablation) |
| x_cf.png # counterfactual edit (flips the ground truth) |
| x_dagger.png # artifact-matched null edit (same operator, no truth change) |
| cf_meta.json # per-instance edit metadata (region, method, target value/state) |
| |
| verdicts/ |
| e0/{oracle,text_only}/<dataset>/verdicts_<split>.jsonl # E0 positive-control verdicts |
| pilot/<judge_id>/<dataset>/verdicts_<split>.jsonl # E1 main-audit verdicts (every judge x image condition x trace condition) |
| e2_extended/<judge_id>/<dataset>/verdicts_<split>.jsonl # independent E2 candidate-pool verdicts (ChartQA, ScienceQA only) |
| |
| injected/<dataset>/injected_<split>.jsonl # clean/visual-error/logical-error trace text per instance |
| traces/<dataset>/traces_<split>.jsonl # clean trace text per instance (pre-injection) |
| data_processed/<dataset>/instances_<split>.jsonl # ingested ground-truth instances (the common schema every downstream stage reads) |
| ``` |
|
|
| ## Datasets included |
|
|
| | Dataset | Split | n (in paper) | Status | |
| |---|---|---|---| |
| | ChartQA | val | 100 | in paper | |
| | HallusionBench | val | 104 | in paper | |
| | MathVista | testmini | 16 | in paper (FigureQA-sourced bar-comparison subset) | |
| | ScienceQA | test | 22 | in paper (State-capitals subset) | |
| | GQA | val | -- | **excluded negative result** — construction plateaued at 70% human-validated edit-validity, below the 95% pre-registered bar. Images/edits released for inspection per the paper's reproducibility statement, but GQA does not appear in any reported table. | |
|
|
| ## Judges covered in `verdicts/` |
|
|
| `llava_onevision_7b`, `qwen25vl_7b`, `internvl3_8b`, `llama32_vision_11b`, |
| `gpt4o_class`, `gemini_class`, `claude_class`, `visualprm_8b` (plus |
| `_text_only` variants where applicable), and the `oracle`/`text_only` |
| E0 reference judges. |
|
|
| ## Reproducing a number from this data |
|
|
| Each `verdicts/pilot/<judge_id>/<dataset>/verdicts_<split>.jsonl` file has |
| one row per `(instance_id, condition, trace_condition)` with the judge's |
| `verdict`/`score`. Feed it through `groundjudge/src/metrics_glue.py`'s |
| `run_audit()` (in the code repo) to reproduce the exact VGS/GEDR/LEDR/CI |
| numbers in Table 1 — this is the same function that produced them originally. |
|
|
