|
--- |
|
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dataset, except the input source documents of its `test` split have been replaced by a __dense__ retriever.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__: `"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==20` |
|
|
|
Retrieval results on the `train` set: |
|
|
|
| Recall@100 | Rprec | Precision@k | Recall@k | |
|
| ----------- | ----------- | ----------- | ----------- | |
|
| 0.5270 | 0.2005 | 0.0573 | 0.3785 | |
|
|
|
Retrieval results on the `validation` set: |
|
|
|
| Recall@100 | Rprec | Precision@k | Recall@k | |
|
| ----------- | ----------- | ----------- | ----------- | |
|
| 0.5310 | 0.2026 | 0.059 | 0.3831 | |
|
|
|
Retrieval results on the `test` set: |
|
|
|
| Recall@100 | Rprec | Precision@k | Recall@k | |
|
| ----------- | ----------- | ----------- | ----------- | |
|
| 0.5229 | 0.2081 | 0.058 | 0.3794 | |