Card: cite the IdeaLens paper only

README.md

@@ -98,9 +98,10 @@ The paraphrase keeps every item's role, order and content, and changes only the
 ## How the corpus was built
 
 - **Documents and labels.** Documents are English Common Crawl pages from the 2024, 2025 and 2026 crawls, drawn from
-  the WildAI corpus (citation below), which builds on FineWeb and annotates each page with a WebOrganizer format and topic and a Pangram authorship prediction. We kept documents of
-  at least 500 words, in eight long-form formats, that Pangram labels as entirely human-written or entirely
-  AI-generated. Documents Pangram labels as mixed or AI-assisted were left out.
+  the WildAI corpus, which builds on FineWeb and annotates each page with a WebOrganizer format and topic and a
+  Pangram authorship prediction. We kept documents of at least 500 words, in eight long-form formats, that Pangram
+  labels as entirely human-written or entirely AI-generated. Documents Pangram labels as mixed or AI-assisted were left
+  out. The paper describes the construction in full.
 - **Outline extraction.** For each format, a role vocabulary lists the recurring functions an idea can serve in that
   kind of document. An LLM, given the document, its format's role vocabulary and six worked examples, writes the
   outline. Most documents were extracted by `gemini-3.7-flash`; part of the corpus, from an earlier build, by
@@ -163,36 +164,11 @@ with Google Gemini models.
 ## Citation
 
 ```bibtex
-@misc{idealens2026,
-  title  = {IdeaLens},
-  author = {Anonymous},
-  year   = {2026},
-  note   = {Citation added on publication}
-}
-```
-
-## Sources
-
-The documents and their Pangram labels come from WildAI, which builds on FineWeb; the formats and topics are
-WebOrganizer's.
-
-```bibtex
-@misc{wildai2026,
-  title  = {Scaling Laws for Wild {AI} Text in Pretraining Data},
-  author = {Anonymous},
-  year   = {2026},
-  note   = {Citation added on publication}
-}
-@inproceedings{penedo2024fineweb,
-  title     = {The {FineWeb} Datasets: Decanting the Web for the Finest Text Data at Scale},
-  author    = {Guilherme Penedo and Hynek Kydl{\'\i}{\v{c}}ek and Loubna Ben allal and Anton Lozhkov and Margaret Mitchell and Colin Raffel and Leandro Von Werra and Thomas Wolf},
-  booktitle = {The Thirty-eighth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
-  year      = {2024}
-}
-@inproceedings{wettig2025organize,
-  title     = {Organize the Web: Constructing Domains Enhances Pre-Training Data Curation},
-  author    = {Alexander Wettig and Kyle Lo and Sewon Min and Hannaneh Hajishirzi and Danqi Chen and Luca Soldaini},
-  booktitle = {Forty-second International Conference on Machine Learning},
-  year      = {2025}
+@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}
 }
 ```