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--- |
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annotations_creators: |
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- expert-generated |
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language_creators: |
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- expert-generated |
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language: |
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- en |
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license: |
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- apache-2.0 |
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multilinguality: |
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- monolingual |
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size_categories: |
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- 10K<n<100K |
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source_datasets: |
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- extended|other-MS^2 |
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- extended|other-Cochrane |
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task_categories: |
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- summarization |
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- text2text-generation |
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task_ids: [] |
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paperswithcode_id: multi-document-summarization |
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pretty_name: MSLR Shared Task |
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tags: |
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- query-based-summarization |
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- query-based-multi-document-summarization |
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- scientific-document-summarization |
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--- |
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This is a copy of the [MS^2](https://huggingface.co/datasets/allenai/mslr2022) dataset, except the input source documents of its `validation` split have been replaced by a __sparse__ retriever. The retrieval pipeline used: |
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|
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- __query__: The `background` field of each example |
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- __corpus__: The union of all documents in the `train`, `validation` and `test` splits. A document is the concatenation of the `title` and `abstract`. |
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- __retriever__: BM25 via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) with default settings |
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- __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 |
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Retrieval results on the `validation` set: |
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|
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|ndcg | recall@100 | recall@1000 | Rprec | |
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| ----------- | ----------- | ----------- | ----------- | |
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| 0.4012 | 0.3780 | 0.6601 | 0.1833 | |
