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Update Readme with arxiv citation key

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@@ -87,6 +87,24 @@ ds_filtered = ds["train"].filter(lambda x: x["revenue"] is not None)
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  - **OCR text**: DeepSeek OCR applied to annual report PDFs from SEC EDGAR, LSE, ASX, and other exchanges.
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  - **KPI values**: SEC EDGAR (XBRL companyfacts) for US listings; yfinance for non-US; Alpha Vantage for gap-fill.
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- ## Citation
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- If you use this dataset, please cite LEDGER (citation key comming soon).
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - **OCR text**: DeepSeek OCR applied to annual report PDFs from SEC EDGAR, LSE, ASX, and other exchanges.
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  - **KPI values**: SEC EDGAR (XBRL companyfacts) for US listings; yfinance for non-US; Alpha Vantage for gap-fill.
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+ ## Citation key
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+ If you use LEDGER datasets and / or code ressources, please consider citing our work with:
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+
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+ ```
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+ @misc{moslonka2026ledgerlongcontextbenchmarkcorporate,
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+ title={LEDGER: A Long-Context Benchmark of Corporate Annual Reports for Grounded Financial Retrieval and Extraction},
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+ author={Charles Moslonka and Amaury de Vitry and Arthur Garnier and Hicham Randrianarivo and Emmanuel Malherbe},
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+ year={2026},
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+ eprint={2606.13100},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2606.13100},
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+ }
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+ ```
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+
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+ ## Links
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+ - **Collection**: [artefactory/ledger](https://huggingface.co/collections/artefactory/ledger)
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+ - **Code**: [github.com/artefactory/LEDGER](https://github.com/artefactory/LEDGER)
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+ - **ArXiv** [https://arxiv.org/abs/2606.13100](https://arxiv.org/abs/2606.13100)