Unsupervised Opinion Summarization as Copycat-Review Generation A Bražinskas, M Lapata, I Titov ACL 2020, 2020 | 120 | 2020 |
Few-Shot Learning for Opinion Summarization A Bražinskas, M Lapata, I Titov EMNLP 2020, 2020 | 66 | 2020 |
Embedding words as distributions with a Bayesian skip-gram model A Bražinskas, S Havrylov, I Titov COLING 2018, 1775--1789, 2018 | 52 | 2018 |
Learning Opinion Summarizers by Selecting Informative Reviews A Bražinskas, M Lapata, I Titov EMNLP 2021, 2021 | 22 | 2021 |
Efficient Few-Shot Fine-Tuning for Opinion Summarization A Bražinskas, R Nallapati, M Bansal, M Dreyer NAACL Findings 2022, 2022 | 16 | 2022 |
Beyond Opinion Mining: Summarizing Opinions of Customer Reviews RK Amplayo, A Bražinskas, Y Suhara, X Wang, B Liu SIGIR tutorial 2022, 2022 | 13* | 2022 |
Interactive-chain-prompting: Ambiguity resolution for crosslingual conditional generation with interaction J Pilault, X Garcia, A Bražinskas, O Firat arXiv preprint arXiv:2301.10309, 2023 | 10 | 2023 |
Small language models improve giants by rewriting their outputs G Vernikos, A Bražinskas, J Adamek, J Mallinson, A Severyn, E Malmi arXiv preprint arXiv:2305.13514, 2023 | 7 | 2023 |
Transductive learning for abstractive news summarization A Bražinskas, M Liu, R Nallapati, S Ravi, M Dreyer arXiv preprint arXiv:2104.09500, 2021 | 2 | 2021 |
Low-and high-resource opinion summarization A Bražinskas The University of Edinburgh, 2023 | 1 | 2023 |