| --- |
| task_categories: |
| - text-generation |
| --- |
| |
| # MedMCQA-50 |
|
|
| This dataset expands |
| [`rohan2810/medmcqa`](https://huggingface.co/datasets/rohan2810/medmcqa) |
| from 20 to 50 candidates per example for finite-pool preference-optimization |
| experiments. |
|
|
| ## Construction |
|
|
| For every example, all unique candidates in the original 20-entry pool are |
| preserved. Duplicate answer strings in the source are collapsed while retaining |
| their first occurrence. Additional distractors are sampled deterministically |
| from the 172,635-answer source candidate universe |
| using seed `1958` until each row has exactly 50 unique candidates. |
| The resulting candidates are deterministically shuffled, and the candidate list |
| embedded in `fixed_prompt` is replaced accordingly. |
|
|
| No model scores, embeddings, selector objectives, or evaluation outcomes are |
| used to construct the candidate pools. This nested construction limits |
| dataset-generation confounding when studying a larger candidate pool. |
|
|
| ## Splits |
|
|
| - `train`: 98,864 rows |
| - `validation`: 12,358 rows |
| - `test`: 12,359 rows |
|
|
| Each row contains: |
|
|
| - `fixed_prompt`: the medical question and the same 50 answer candidates. |
| - `itemList`: 50 unique answer candidates. |
| - `trueSelection`: the true answer, appearing exactly once in `itemList`. |
|
|
| ## Provenance |
|
|
| - Source repository: `rohan2810/medmcqa` |
| - Source revision: `b4944b5c7085a408c24f50f4b2ae8eed0ef66239` |
| - Output repository: `rohan2810/medmcqa50` |
| - Generator seed: `1958` |
| - Generator: `neurips_rebuttal/medmcqa50_dataset/build_medmcqa50.py` |
|
|
