| --- |
| license: apache-2.0 |
| task_categories: |
| - text-generation |
| language: |
| - en |
| pretty_name: Human Study |
| size_categories: |
| - n<1K |
| --- |
| |
| # human_study |
| |
| Free-form human Reddit responses derived from |
| [`snap-stanford/user_study_annotations`](https://huggingface.co/datasets/snap-stanford/user_study_annotations). |
| The original Reddit post text comes from the HumanLM authors' |
| [`reddit_post_dict_testset.json`](https://github.com/zou-group/humanlm/blob/6faaf072b14b3efb4d434237d6d2af13f7a91d00/user_study/data/reddit_post_dict_testset.json). |
| |
| Each row contains an original Reddit post in `prompt` and the response written |
| by a human-study participant in `target`. Model responses, generated personas, |
| comparison judgments, and worker identifiers are intentionally excluded. |
| |
| ## Deduplication and splits |
| |
| - Source annotation revision: `b19978763f7a1e4fcf71c2facfa65af0136cc425` |
| - Random seed: `42` |
| - Exactly one annotation is randomly selected per unique `post_id`. |
| - `post_id` is unique across the complete derived dataset. |
| - The 5 most compact selected rows form the few-shot `train` |
| split to keep prompts within small model context windows. |
| - All remaining unique posts form the scored `test` split. |
| - Train rows: 5 |
| - Test rows: 59 |
|
|
| The prompt contract is: |
|
|
| ```text |
| Post: |
| <original Reddit post> |
| |
| Response:<SPACE> |
| ``` |
|
|
| The `Response:` cue ends with exactly one ASCII space so lm-eval can append |
| few-shot targets and begin generation at a natural token boundary. The target |
| is the participant's original free-form response. |
|
|
