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metadata
annotations_creators:
  - found
language_creators:
  - found
language:
  - en
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - summarization
task_ids:
  - summarization-other-paper-abstract-generation
paperswithcode_id: multi-xscience
pretty_name: Multi-XScience

This is a copy of the Multi-XScience dataset, except the input source documents of its test split have been replaced by a sparse retriever. The retrieval pipeline used:

  • query: The related_work field of each example
  • corpus: The union of all documents in the train, validation and test splits
  • retriever: BM25 via PyTerrier with default settings. The number of documents retrieved, k, is set as the original number of input documents for each example.

Retrieval results on the test set:

ndcg recall@100 recall@1000 Rprec
0.2327 0.2999 0.3829 0.1452