Datasets:

rishanthrajendhran
/

IdeaShift

license: other
license_name: mixed-see-card
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, 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 package (PyPI) 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.

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 and are subject to OpenAI's terms. Detector scores and annotations are released under CC BY 4.0.

Citation

@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}
}