
This is a copy of the [Cochrane](https://huggingface.co/datasets/allenai/mslr2022) dataset, except the input source documents of its `train`, `validation` and `test` splits have been replaced by a __dense__ retriever. The retrieval pipeline used:

- __query__: The `target` field of each example
- __corpus__: The union of all documents in the `train`, `validation` and `test` splits. A document is the concatenation of the `title` and `abstract`.
- __retriever__: [`facebook/contriever-msmarco`](https://huggingface.co/facebook/contriever-msmarco) via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) 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==9`

Retrieval results on the `train` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.7790 | 0.4487 | 0.3438 | 0.4800 |

Retrieval results on the `validation` set:

| Recall@100 | Rprec | Precision@k | Recall@k |
| ----------- | ----------- | ----------- | ----------- |
| 0.7856 | 0.4424 | 0.3534 | 0.4913 |

Retrieval results on the `test` set:

N/A. Test set is blind so we do not have any queries.
task_categories:summarization task_categories:text2text-generation annotations_creators:expert-generated language_creators:expert-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:extended|other-MS^2 source_datasets:extended|other-Cochrane language:en license:apache-2.0 region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["expert-generated"], "language": ["en"], "license": ["apache-2.0"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["extended|other-MS^2", "extended|other-Cochrane"], "task_categories": ["summarization", "text2text-generation"], "paperswithcode_id": "multi-document-summarization", "pretty_name": "MSLR Shared Task"}
TAGS
#task_categories-summarization #task_categories-text2text-generation #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|other-MS^2 #source_datasets-extended|other-Cochrane #language-English #license-apache-2.0 #region-us 

This is a copy of the Cochrane dataset, except the input source documents of its 'train', 'validation' and 'test' splits have been replaced by a **dense** retriever. The retrieval pipeline used:


* **query**: The 'target' field of each example
* **corpus**: The union of all documents in the 'train', 'validation' and 'test' splits. A document is the concatenation of the 'title' and 'abstract'.
* **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==9'


Retrieval results on the 'train' set:



Retrieval results on the 'validation' set:



Retrieval results on the 'test' set:


N/A. Test set is blind so we do not have any queries.



TAGS
#task_categories-summarization #task_categories-text2text-generation #annotations_creators-expert-generated #language_creators-expert-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-extended|other-MS^2 #source_datasets-extended|other-Cochrane #language-English #license-apache-2.0 #region-us 
