Discriminative Marginalized Probabilistic Neural Method for Multi-Document Summarization of Medical Literature
Gianluca Moro, Luca Ragazzi, Lorenzo Valgimigli, Davide Freddi
Abstract
Although current state-of-the-art Transformer-based solutions succeeded in a wide range for single-document NLP tasks, they still struggle to address multi-input tasks such as multi-document summarization. Many solutions truncate the inputs, thus ignoring potential summary-relevant contents, which is unacceptable in the medical domain where each information can be vital. Others leverage linear model approximations to apply multi-input concatenation, worsening the results because all information is considered, even if it is conflicting or noisy with respect to a shared background. Despite the importance and social impact of medicine, there are no ad-hoc solutions for multi-document summarization. For this reason, we propose a novel discriminative marginalized probabilistic method (DAMEN) trained to discriminate critical information from a cluster of topic-related medical documents and generate a multi-document summary via token probability marginalization. Results prove we outperform the previous state-of-the-art on a biomedical dataset for multi-document summarization of systematic literature reviews. Moreover, we perform extensive ablation studies to motivate the design choices and prove the importance of each module of our method.- Anthology ID:
- 2022.acl-long.15
- Volume:
- Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Smaranda Muresan, Preslav Nakov, Aline Villavicencio
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 180–189
- Language:
- URL:
- https://aclanthology.org/2022.acl-long.15
- DOI:
- 10.18653/v1/2022.acl-long.15
- Cite (ACL):
- Gianluca Moro, Luca Ragazzi, Lorenzo Valgimigli, and Davide Freddi. 2022. Discriminative Marginalized Probabilistic Neural Method for Multi-Document Summarization of Medical Literature. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 180–189, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- Discriminative Marginalized Probabilistic Neural Method for Multi-Document Summarization of Medical Literature (Moro et al., ACL 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.acl-long.15.pdf