| --- |
| license: cc-by-nc-sa-4.0 |
| language: |
| - en |
| tags: |
| - ai-text-detection |
| - idea-provenance |
| pretty_name: IdeaShift |
| size_categories: |
| - 1K<n<10K |
| extra_gated_prompt: "Access is granted individually. Please say who you are and what you intend to use the data for." |
| configs: |
| - config_name: default |
| data_files: |
| - split: source |
| path: data/source.parquet |
| - split: level_0 |
| path: data/level_0.parquet |
| - split: level_1 |
| path: data/level_1.parquet |
| - split: level_2 |
| path: data/level_2.parquet |
| - split: level_3 |
| path: data/level_3.parquet |
| - split: level_4 |
| path: data/level_4.parquet |
| - split: level_5 |
| path: data/level_5.parquet |
| --- |
| |
| # IdeaShift |
|
|
| IdeaShift measures whether an AI-text detector tracks **who came up with a document's ideas** or **who wrote its |
| prose**. It holds 500 seed documents and, for each, six documents written by GPT-5.6 models from prompts that carry |
| progressively more of the seed's plan. All 3,000 generated documents are AI-written prose. When the seed is |
| human-written, the later levels carry more and more of a person's ideas. |
|
|
| ## Construction |
|
|
| - **Seeds:** 500 English web documents from the test split of |
| [WildOutlines](https://huggingface.co/datasets/rishanthrajendhran/WildOutlines), 62-63 per format across eight |
| long-form formats. 237 are human-written and 263 AI-generated, per the Pangram silver labels of that corpus. |
| - **Prompts:** for each seed, GPT-5.6 Sol wrote a prompt at each level: |
|
|
| | Level | The prompt gives | |
| |---|---| |
| | 0 | the document type only | |
| | 1 | a very high-level focus | |
| | 2 | the seed's global themes | |
| | 3 | themes and the sequence of roles | |
| | 4 | themes and the full outline, as a plan to follow | |
| | 5 | the seed's full role-labelled outline, with an instruction to add nothing else | |
|
|
| - **Generation:** one GPT-5.6 model per seed (Sol for 250 seeds, Terra for 125, Luna for 125) wrote a document from |
| each prompt. |
|
|
| An idea detector should flag every document from an AI seed. On human seeds it should flag fewer documents as the |
| level rises, because more of the ideas come from the person. A prose detector should flag every generated document. |
|
|
| ## Splits |
|
|
| | Split | Rows | What it holds | |
| |---|---:|---| |
| | `source` | 500 | the seed documents: 237 human-written, 263 AI-generated (`seed_author`) | |
| | `level_0` | 500 | one document per seed, written from the document type only | |
| | `level_1` | 500 | ... from a very high-level focus | |
| | `level_2` | 500 | ... from the seed's global themes | |
| | `level_3` | 500 | ... from the themes and the sequence of roles | |
| | `level_4` | 500 | ... from the themes and the full outline, as a plan to follow | |
| | `level_5` | 500 | ... from the seed's full outline, with an instruction to add nothing else | |
|
|
| Rows in different splits share `seed_id`. `load_dataset("rishanthrajendhran/IdeaShift", split="level_5")` loads one level. |
|
|
| ## Fields |
|
|
| | Field | Description | |
| |---|---| |
| | `id` | document id; generated documents are `<seed_id>\|<condition>` | |
| | `seed_id` | the seed document | |
| | `level` | 0-5 for generated documents; null for the seed itself | |
| | `level_name` | what the prompt carried | |
| | `seed_author` | `human` or `ai`: who wrote the seed (Pangram silver label) | |
| | `prose_author` | who wrote this document's prose (`ai` for every generated document) | |
| | `generator` | the GPT-5.6 model that wrote the document | |
| | `system_prompt`, `prompt` | the exact generation request | |
| | `format`, `topic` | WebOrganizer format and topic of the seed | |
| | `words`, `text` | the document | |
| | `outline` | the paraphrased, role-labelled outline IdeaLens scored (JSON string) | |
| | `idealens_p_ai`, `proselens_p_ai`, `pangram4_p_ai` | detector P(AI) as reported in the paper | |
|
|
| ## Caveats |
|
|
| - Seed labels are Pangram's silver labels of the whole page, not ground truth about how each page was written. |
| - A level describes what the prompt contained, not a measured share of human ideas. |
|
|
| ## Scoring |
|
|
| The [idealens](https://github.com/RishanthRajendhran/IdeaLens) package ([PyPI](https://pypi.org/project/idealens/)) runs IdeaLens, ProseLens and the other released detectors on these documents: `pip install idealens`, then `idealens run` on a JSONL file with a `text` field. |
|
|
| All IdeaLens models and datasets are in the [IdeaLens collection](https://huggingface.co/collections/rishanthrajendhran/idealens-6abee785ce6196fc0be9200f). |
|
|
| ## License |
|
|
| The dataset is released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/): free to share and adapt for non-commercial purposes, with attribution and under |
| the same license. The seed text comes from FineWeb (ODC-By 1.0) and remains subject to the terms of its original |
| sources and of Common Crawl. The generated documents and prompts were produced with OpenAI models. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @article{idealens2026, |
| title = {IdeaLens: Detecting AI Ideas in Long-form Writing}, |
| author = {Anonymous}, |
| journal = {arXiv preprint arXiv:TBD}, |
| year = {2026}, |
| url = {https://arxiv.org/abs/TBD} |
| } |
| ``` |
|
|
