allenai/multinews_dense_max

This is a copy of the Multi-News dataset, except the input source documents of its test split have been replaced by a dense retriever.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

• query: The summary field of each example
• corpus: The union of all documents in the train, validation and test splits
• retriever: facebook/contriever-msmarco via PyTerrier with default settings
• top-k strategy: "max", i.e. the number of documents retrieved, k, is set as the maximum number of documents seen across examples in this dataset, in this case k==10

Retrieval results on the train set:

Recall@100	Rprec	Precision@k	Recall@k
0.8661	0.6867	0.2118	0.7966

Retrieval results on the validation set:

Recall@100	Rprec	Precision@k	Recall@k
0.8626	0.6859	0.2083	0.7949

Retrieval results on the test set:

Recall@100	Rprec	Precision@k	Recall@k
0.8625	0.6927	0.2096	0.7971