| | --- |
| | annotations_creators: |
| | - found |
| | language_creators: |
| | - found |
| | language: |
| | - en |
| | license: |
| | - unknown |
| | multilinguality: |
| | - monolingual |
| | size_categories: |
| | - 10K<n<100K |
| | source_datasets: |
| | - original |
| | task_categories: |
| | - summarization |
| | paperswithcode_id: multi-xscience |
| | pretty_name: Multi-XScience |
| | --- |
| | |
| | This is a copy of the [Multi-XScience](https://huggingface.co/datasets/multi_x_science_sum) dataset, except the input source documents of the `train`, `validation`, and `test` splits have been replaced by a __dense__ retriever.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__: [`facebook/contriever-msmarco`](https://huggingface.co/facebook/contriever-msmarco) via [PyTerrier](https://pyterrier.readthedocs.io/en/latest/) with default settings |
| | - __top-k strategy__: `"oracle"`, i.e. the number of documents retrieved, `k`, is set as the original number of input documents for each example |
| |
|
| | Retrieval results on the `train` set: |
| |
|
| | | Recall@100 | Rprec | Precision@k | Recall@k | |
| | | ----------- | ----------- | ----------- | ----------- | |
| | | 0.5270 | 0.2005 | 0.2005 | 0.2005 | |
| |
|
| | Retrieval results on the `validation` set: |
| |
|
| | | Recall@100 | Rprec | Precision@k | Recall@k | |
| | | ----------- | ----------- | ----------- | ----------- | |
| | | 0.5310 | 0.2026 | 0.2026 | 0.2026 | |
| |
|
| | Retrieval results on the `test` set: |
| |
|
| | | Recall@100 | Rprec | Precision@k | Recall@k | |
| | | ----------- | ----------- | ----------- | ----------- | |
| | | 0.5229 | 0.2081 | 0.2081 | 0.2081 | |
