| monot5-3b-inpars-v2-trec-covid-promptagator is a monoT5-3B model finetuned on TREC-COVID synthetic data generated by [InPars](https://github.com/zetaalphavector/inPars). | |
| Currently, if you use this tool you can cite the original [InPars paper published at SIGIR](https://dl.acm.org/doi/10.1145/3477495.3531863) or [InPars-v2](https://arxiv.org/abs/2301.01820). | |
| ``` | |
| @inproceedings{inpars, | |
| author = {Bonifacio, Luiz and Abonizio, Hugo and Fadaee, Marzieh and Nogueira, Rodrigo}, | |
| title = {{InPars}: Unsupervised Dataset Generation for Information Retrieval}, | |
| year = {2022}, | |
| isbn = {9781450387323}, | |
| publisher = {Association for Computing Machinery}, | |
| address = {New York, NY, USA}, | |
| url = {https://doi.org/10.1145/3477495.3531863}, | |
| doi = {10.1145/3477495.3531863}, | |
| booktitle = {Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval}, | |
| pages = {2387–2392}, | |
| numpages = {6}, | |
| keywords = {generative models, large language models, question generation, synthetic datasets, few-shot models, multi-stage ranking}, | |
| location = {Madrid, Spain}, | |
| series = {SIGIR '22} | |
| } | |
| ``` | |
| ``` | |
| @misc{inparsv2, | |
| doi = {10.48550/ARXIV.2301.01820}, | |
| url = {https://arxiv.org/abs/2301.01820}, | |
| author = {Jeronymo, Vitor and Bonifacio, Luiz and Abonizio, Hugo and Fadaee, Marzieh and Lotufo, Roberto and Zavrel, Jakub and Nogueira, Rodrigo}, | |
| title = {{InPars-v2}: Large Language Models as Efficient Dataset Generators for Information Retrieval}, | |
| publisher = {arXiv}, | |
| year = {2023}, | |
| copyright = {Creative Commons Attribution 4.0 International} | |
| } | |
| ``` | |