| --- |
| language: |
| - vi |
| - en |
| pretty_name: ViHiX |
| license: cc-by-nc-4.0 |
| task_categories: |
| - visual-question-answering |
| - question-answering |
| - image-text-to-text |
| tags: |
| - vietnamese |
| - exam |
| - education |
| - multimodal |
| - benchmark |
| size_categories: |
| - 1K<n<10K |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-*.parquet |
| --- |
| |
| # ViHiX: Vietnam High-school Examination Benchmark |
|
|
| A multimodal (text + image) benchmark of **3,006 questions** from **84 official exam papers** of Vietnam's national high-school examinations (the *THPT Quốc gia* exam in 2018–2019 and the *Tốt nghiệp THPT* graduation exam in 2020–2026), covering **13 subjects**. The questions are in Vietnamese. Each question contains the text transcribed verbatim from the original paper, an answer checked against the **official answer key published by the Ministry of Education and Training (MoET)**, **cropped images** for the 199 questions that rely on a figure, graph, diagram or table, and, for the 96 Geography questions that require the Vietnam Atlas, **crops of the relevant Atlas map region** (plus the matching symbol-legend rows when the page has no legend). |
|
|
| Intended uses: |
| - Evaluating (multimodal) language models on real Vietnamese exam questions, scored against official answers. |
| - Generating and filtering chain-of-thought data using the official answers as ground truth. |
| - Evaluating document and exam extraction from scanned PDFs. |
|
|
| ## Statistics |
|
|
| Questions per subject and year. For every (year, subject) pair we include **one representative exam code** (`ma_de`), since the different codes of the same exam are permutations of the same questions. |
|
|
| | Subject | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | Total | |
| |---|---|---|---|---|---|---|---|---|---|---| |
| | English | 50 | 50 | 50 | 50 | 50 | 50 | 50 | 40 | 40 | 430 | |
| | Mathematics | 50 | 50 | 50 | 50 | 50 | 50 | 50 | 22 | 22 | 394 | |
| | History | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 28 | 28 | 336 | |
| | Biology | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 28 | 28 | 336 | |
| | Chemistry | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 28 | 28 | 336 | |
| | Physics | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 28 | 28 | 336 | |
| | Geography | 40 | 40 | 40 | 40 | 40 | 40 | 40 | 28 | 28 | 336 | |
| | Civic Education (GDCD) | 40 | 40 | 40 | 40 | 40 | 40 | 40 | – | – | 280 | |
| | Informatics | – | – | – | – | – | – | – | 30 | 30 | 60 | |
| | Economics and Law Education (GDKTPL) | – | – | – | – | – | – | – | 28 | 28 | 56 | |
| | Literature (Ngữ văn) | – | 6 | 6 | 6 | 6 | 6 | 6 | 7 | 7 | 50 | |
| | Technology (Agriculture track) | – | – | – | – | – | – | – | 28 | – | 28 | |
| | Technology (Industry track) | – | – | – | – | – | – | – | 28 | – | 28 | |
|
|
| - Question types: `mcq`: 2,820, `true_false`: 76, `short_answer`: 60, `essay`: 50 |
| - Questions with images: 295 (199 with figures from the paper, 96 with Atlas crops: 135 map crops and 33 legend crops). |
| - Questions usable as ground truth (`gt_usable`): 2,909 (listed in `cot_ready.jsonl`). |
| - Subjects that rely on images the most: Technology (Industry track) ~43% of questions, Geography ~34% (5% figures, 29% Atlas crops), Mathematics ~17%, Biology ~14%, Physics ~11%, Chemistry ~5%. English, History, Civic Education, Economics and Law, Informatics, Technology (Agriculture track) and Literature are text-only. |
|
|
| Not included: foreign languages other than English (French, Russian, Chinese, German, Japanese, Korean). |
|
|
| ## Data format |
|
|
| | Column | Description | |
| |---|---| |
| | `id` | `<exam_id>_<part><number>`, unique | |
| | `exam_id`, `year`, `exam_type`, `subject`, `subject_name`, `ma_de` | Exam, year, exam type (`THPTQG` for 2018–2019, `TNTHPT` for 2020–2026), subject (short code / Vietnamese name), exam code | |
| | `global_no`, `part`, `q_no` | Running index 1..N within the exam, section (I/II/III), and the question number printed on the paper | |
| | `q_type` | `mcq` (four options), `true_false` (four statements a–d), `short_answer`, `essay` (Literature) | |
| | `passage` | Shared reading passage or data (repeated for every question that uses it) | |
| | `question` | Question text (formulas as LaTeX inside `$...$`) | |
| | `option_A..D`, `statement_a..d` | Answer options (`mcq`) or statements (`true_false`) | |
| | `answer` | `mcq`: `A`–`D`; `true_false`: `Đ,S,Đ,S` (Đúng/true, Sai/false, in the order a–d); `short_answer`: a number string as in the official key (decimal comma; may be several values such as `"8000; 8002"`); `essay`: `null` | |
| | `answer_status` | `official` (MoET key) or `none` (not available or deliberately withheld) | |
| | `key_debatable` | `true` for 8 questions where the official key may be debatable: an LLM solving blind chose the same other answer in all 5 independent attempts, even though the transcription and the key were re-checked against the original paper. The official answer is kept as ground truth | |
| | `gt_usable` | `true` if the question can be used as ground truth: it has an official MoET answer and no known problem (excludes the 50 Literature essays, Geography 2021, 3 questions under review and 4 whose figure is missing from the source paper). 2,909 questions | |
| | `image`, `images` / `image_paths` | Parquet: embedded images (`image` = first image). JSON/CSV: paths inside `images/`. Images are figures from the paper and, for Geography questions that cite the Vietnam Atlas, crops of the relevant Atlas region (`atlas_*_k.jpg`) and symbol legend (`atlas_*_L.jpg`) | |
| | `source_file`, `page`, `notes` | Source file, page, and extraction notes (for example printing errors in the original paper) | |
|
|
| Formats: `data/*.parquet` (images embedded, for `load_dataset`), `data.jsonl`, `data.json` and `data.csv` (images referenced through `image_paths` inside the `images/` folder). |
|
|
| ```python |
| from datasets import load_dataset |
| ds = load_dataset("quin210/ViHiX", split="train") |
| ds = ds.filter(lambda x: x["gt_usable"]) |
| ``` |
|
|
| ## Worked solutions |
|
|
| `solutions.jsonl` holds step-by-step worked solutions in Vietnamese for **all 2,909** `gt_usable` questions. One line per question: `{"id", "solution", "answer", "model_answer", "confidence", "atlas_free", "answer_given", "key_debatable", "doubt"?}`. |
|
|
| | Subset | Questions | How the solution was produced | |
| |---|---|---| |
| | `answer_given = false` | 2,897 | LLM solved the question **without seeing the answer** (for the 81 Atlas questions, reading the Atlas page); kept only because its final answer matches the official MoET answer. For hard questions up to 5 independent blind attempts were made | |
| | `answer_given = true` | 12 | The model got these wrong in all 5 blind attempts (the transcription and the official key were re-checked against the original paper). The solution was then written **with the official answer given**, explaining why it is correct and why the tempting options are wrong. `model_answer` keeps the model's earlier blind answer | |
|
|
| - Median solution length ~710 characters; calculation subjects state the data, formulas and intermediate results, and theory subjects discuss every option or statement a–d. |
| - Answer matching normalizes the decimal comma/point; `true_false` must match all four statements. |
| - `doubt` (1 question, `answer_given`): the model found the official answer hard to justify (Biology 2023 Q113 depends on reading a graph value). |
| - `key_debatable` (8 questions, all `answer_given`): the model chose the *same* other answer in all 5 blind attempts, which may indicate a debatable official key; the official MoET answer is still used as ground truth. |
| - `atlas_free` is kept for compatibility and is `false` everywhere now that Atlas images are attached. The source Atlas scan is ~1170×1650 px per page, so very small labels are sometimes hard to read; such solutions say when they fall back on general knowledge. |
| - `confidence` is the model's own estimate (`high` / `medium` / `low`). |
| - For the cleanest training data, use `answer_given == false` (2,897 questions). |
|
|
| ```python |
| sol = load_dataset("quin210/ViHiX", data_files="solutions.jsonl", split="train") |
| ``` |
|
|
| ## Evaluation protocol |
|
|
| The `eval/` folder contains the official scorer and protocol: |
| - `eval/PROTOCOL.md`: protocol v1.0 (input, prompts, decoding, metrics). |
| - `eval/score.py`: scorer. Run `python eval/score.py predictions.jsonl --data cot_ready.jsonl` with one `{"id": ..., "answer": ...}` per line. |
| - `eval/prompts.json`: fixed zero-shot prompts for each question type. |
|
|
| Metrics: `score_pct` (primary; `ALL_excl_key_debatable` is also reported) uses official-style partial credit, where `true_false` follows the MoET rubric (1 correct statement = 0.1, 2 = 0.25, 3 = 0.5, 4 = 1.0), `mcq` and `short_answer` are 0/1; `exact_pct` is strict exact match. A missing or unparsable answer counts as 0. Reports are broken down by subject, question type, exam type, image vs text-only, and year. |
|
|
| ## How the dataset was built and verified |
|
|
| 1. The papers (PDF/DOC/DOCX, many of them low-quality scans) were converted to page images. A vision model transcribed **each page** verbatim, including printing errors in the original, and figures or tables were cropped by coordinates and checked one by one. |
| 2. Answers were taken from the **images of the official MoET answer keys**, using the column of the right exam code. "Reference answers" published by third parties were **not** used as ground truth. When a key file was missing from the collection, the official table was found online (re-published by several news outlets) and cross-checked. An older OCR-derived answer set was found to contain many errors and was discarded. |
| 3. **Answer keys were read twice independently.** Every key was read at least twice by separate passes (the second pass did not see the first pass's answers) and compared programmatically; every disagreement was resolved by re-reading the zoomed-in official table and checking the content of the question. This process corrected 5 wrong answers. |
| 4. **Independent spot check.** A separate group of reviewers re-read the exam images before looking at the JSON for all doubtful questions plus 6 random questions per exam (about 480 questions). About 1% had small transcription errors (a wrong word, an extra crop), all fixed. |
| 5. **Solution-disagreement review.** Every question whose model solution disagreed with the official answer was re-checked against the original paper. This found and fixed transcription errors (swapped options, missing "not", wrong numbers, a wrong figure) and a systematic problem in English: many questions had lost the printed instruction line (e.g. "CLOSEST/OPPOSITE in meaning") and underlines. All English questions (2018–2026) were then re-checked against the originals and fixed. No official answer was changed except one disputed key resolved from the MoET table image. |
| 6. Every exam passes an automatic schema check (all questions present, all options present, valid answers, images exist, warnings when a question mentions a figure but has no image). |
|
|
| ## Source and license |
|
|
| The exam papers and answer keys are documents of Vietnam's Ministry of Education and Training, collected from public sources. The Atlas crops are short excerpts of the *Atlat Địa lí Việt Nam* (Vietnam Education Publishing House), included for education and research. The dataset (transcriptions, annotations, flags and worked solutions) is released under **CC BY-NC 4.0**: non-commercial use with attribution. Rights to the original exam papers and the Atlas remain with their owners. |
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