Update README.md

README.md

@@ -22,6 +22,16 @@ dataset_info:
   download_size: 382068275
   dataset_size: 857168232
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-# Dataset Card for "arxiv_redpajama_2302"
+# ArXiv papers from RedPajama-Data originally published in February 2023
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+We collect the ArXiv papers released shortly before the training data cutoff date for the [OpenLLaMA models](https://huggingface.co/openlm-research/open_llama_7b). 
+
+The OpenLLaMA models (V1) have been trained on [RedPajama data](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T).
+The last batch of ArXiv papers included in this dataset are papers published in February 2023. 
+To get the members close to the cutoff data, we collect the 13,155 papers published in "2302" as part of the training dataset. 
+We process the raw LateX files using this [script](https://github.com/togethercomputer/RedPajama-Data/blob/rp_v1/data_prep/arxiv/run_clean.py). 
+
+This dataset has been used as source for 'member' documents to develop (document-level) MIAs against LLMs using data collected shortly before (member) and after (non-member) the training cutoff date for the target model ([the suite of OpenLLaMA models](https://huggingface.co/openlm-research/open_llama_7b)). 
+For more details and results see the section of Regression Discontiuity Design (RDD) in the paper ["SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)"](https://arxiv.org/pdf/2406.17975).
+
+For non-members for the RDD setup, we refer to our [Github repo](https://github.com/computationalprivacy/mia_llms_benchmark/tree/main/document_level).