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
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
Bibkey:
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)
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PDF:
https://aclanthology.org/2022.acl-long.15.pdf