A Quantum Annealing Instance Selection Approach for Efficient and Effective Transformer Fine-Tuning.
Andrea Pasin|Washington Cunha|Marcos André Gonçalves|Nicola Ferro
| Anthology ID: | DBLP:conf/ictir/PasinCG024 |
|---|---|
| Volume: | Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2024, Washington, DC, USA, 13 July 2024 |
| Year: | 2024 |
| Venue: | International Conference on the Theory of Information Retrieval (ICTIR) |
| Publisher: | ACM |
| Pages: | 205-214 |
| URL: | https://doi.org/10.1145/3664190.3672515 |
| DOI: | https://doi.org/10.1145/3664190.3672515 |
| DBLP: | conf/ictir/PasinCG024 |
| BibTeX: |
@inproceedings{pasin-2024-quantum,
author = {Andrea Pasin and
Washington Cunha and
Marcos Andr\'{e} Gon\c{c}alves and
Nicola Ferro},
editor = {Harrie Oosterhuis and
Hannah Bast and
Chenyan Xiong},
title = {{A Quantum Annealing Instance Selection Approach for Efficient and Effective Transformer Fine-Tuning}},
booktitle = {{Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2024, Washington, DC, USA, 13 July 2024}},
pages = {205--214},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3664190.3672515},
doi = {https://doi.org/10.1145/3664190.3672515}
}