| --- |
| license: apache-2.0 |
| task_categories: |
| - image-to-text |
| - visual-question-answering |
| language: |
| - en |
| size_categories: |
| - n<1K |
| tags: |
| - benchmark |
| - reflection |
| - rectification |
| - text-to-image |
| - visual-reasoning |
| - image-editing |
| pretty_name: R3-Bench |
| --- |
| |
| # R3-Bench: Reason-Reflect-Rectify Benchmark |
|
|
| **Code**: [github.com/xiaomoguhz/R3-Bench](https://github.com/xiaomoguhz/R3-Bench) |
| **Paper**: *Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation* — accepted to ICML 2026. |
|
|
| R³-Bench evaluates **reflective visual generation**: given a generated image and the original prompt, a model must (i) reason about whether the image matches the prompt, (ii) explain any discrepancy, and (iii) propose a rectification action. The benchmark measures two complementary scores: |
|
|
| - **S_ref** — Reflective Verdict Score (verdict + explanation correctness, judged by an LLM) |
| - **S_rect** — Rectification Score (normalised VQA-alignment gain after applying the proposed edit) |
|
|
| ## Contents |
|
|
| | File | Description | |
| |---|---| |
| | `images.tar.gz` | 670 source images (PNG, ~717 MB), organised as `images/{category}/{verdict}/r3b_{idx:06d}.png` | |
|
|
| The 670-sample **prompt + ground-truth JSONL** ships with the code repository at [`r3bench/data/r3bench.jsonl`](https://github.com/xiaomoguhz/R3-Bench/blob/main/r3bench/data/r3bench.jsonl) — labels travel with the eval code so version drift is captured by git. |
|
|
| ## Schema |
|
|
| Each JSONL record: |
|
|
| ```json |
| { |
| "idx": 0, |
| "original_prompt": "a black candle and a white holder", |
| "bad_image": "images/color/false/r3b_000000.png", |
| "answer": false, |
| "explanation": "The white object is a candle, not a holder as specified in the prompt.", |
| "category": "color", |
| "generated_qa": { |
| "yn_question_list": ["Is there a candle in the image?", "..."] |
| } |
| } |
| ``` |
|
|
| | Field | Type | Description | |
| |---|---|---| |
| | `idx` | int | Unique sample id (0–669) | |
| | `original_prompt` | str | The text-to-image prompt | |
| | `bad_image` | str | Image path relative to the data root | |
| | `answer` | bool | Ground-truth verdict: does the image match the prompt? (`false` = mismatch) | |
| | `explanation` | str | Ground-truth discrepancy description (used as S_ref reference) | |
| | `category` | str | Error dimension: color · object · numeracy · spatial · shape · texture · complex · non | |
| | `generated_qa.yn_question_list` | list[str] | Yes/no VQA probes used by the S_rect rectification scorer | |
| |
| ## Category & verdict distribution (670 total) |
| |
| | Category | false (mismatch) | true (match) | Total | |
| |---|---:|---:|---:| |
| | color | 71 | 26 | 97 | |
| | complex | 46 | 48 | 94 | |
| | non | 7 | 42 | 49 | |
| | numeracy | 73 | 23 | 96 | |
| | object | 54 | 17 | 71 | |
| | shape | 72 | 20 | 92 | |
| | spatial | 76 | 25 | 101 | |
| | texture | 49 | 21 | 70 | |
| | **Sum** | **448** | **222** | **670** | |
| |
| `non` = "no error" probe samples (image matches prompt) used to calibrate false-positive reflection. |
| |
| ## Usage |
| |
| ```bash |
| # 1. Download images |
| hf download xiaomoguhzz/R3-Bench-data images.tar.gz \ |
| --repo-type dataset --local-dir /path/to/r3bench-data |
| cd /path/to/r3bench-data && tar -xzf images.tar.gz |
| # → /path/to/r3bench-data/images/{category}/{true,false}/r3b_{idx:06d}.png |
|
|
| # 2. Run the 4-step pipeline (clone the code repo first) |
| git clone https://github.com/xiaomoguhz/R3-Bench && cd R3-Bench |
| export R3BENCH_DATA_DIR=/path/to/r3bench-data |
|
|
| bash scripts/run_reflection.sh 8 qwen2.5vl # Step 1 — reflection |
| bash scripts/run_edit.sh 8 qwen2.5vl qwen_image_2511 # Step 2 — editing |
| bash scripts/eval_reflection.sh qwen2.5vl # Step 3 — S_ref |
| bash scripts/eval_edit.sh qwen2.5vl qwen_image_2511 # Step 4 — S_rect |
| ``` |
| |
| See the [code repo README](https://github.com/xiaomoguhz/R3-Bench) for full pipeline details, supported backends, and how to plug in a custom reflection / editor model. |
| |
| ## Citation |
| |
| ```bibtex |
| @inproceedings{r3bench2026, |
| title={Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation}, |
| booktitle={Proceedings of the International Conference on Machine Learning (ICML)}, |
| year={2026} |
| } |
| ``` |
| |
| ## License |
| |
| Released under the **Apache 2.0** license. Source prompts adapted from T2I-CompBench, GenEval++, and GEdit-Bench under their respective licenses; see the code repository for full attribution. |
| |
