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metadata
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype: int64
    - name: doc_idx
      dtype: string
  splits:
    - name: train
      num_bytes: 76605258
      num_examples: 50000
  download_size: 36641532
  dataset_size: 76605258

ArXiv papers from The Pile for document-level MIAs against for LLMs (split into sequences)

This dataset contains sequences from ArXiv papers randomly sampled from the train (members) and test (non-members) dataset from (the uncopyrighted version of) the Pile. We randomly sample 1,000 documents members and 1,000 non-members, ensuring that the selected documents have at least 5,000 words (any sequences of characters seperated by a white space). This dataset contains the first 25 sequences of 200 words from all the documents made available in full here.

The dataset contains as columns:

  • text: the raw text of the sequence
  • label: binary label for membership (1=member)
  • doc_idx: index allowing to group sequences to the same, original document

The dataset can be used to develop and evaluate document-level MIAs against LLMs trained on The Pile. Target models include the suite of Pythia and GPTNeo models, to be found here. Our understanding is that the deduplication executed on the Pile to create the "Pythia-dedup" models has been only done on the training dataset, suggesting this dataset of members/non-members also to be valid for these models.

For more information we refer to the paper.