LED down the rabbit hole: exploring the potential of global attention for biomedical multi-document summarisation
This work addresses biomedical literature review summarization, but it is incremental as it builds on an existing method with domain-specific modifications.
The authors adapted the PRIMERA model for biomedical multi-document summarization by applying global attention to key entities, analyzing 23 models to identify patterns related to attention mechanisms, training steps, and input configurations.
In this paper we report on our submission to the Multidocument Summarisation for Literature Review (MSLR) shared task. Specifically, we adapt PRIMERA (Xiao et al., 2022) to the biomedical domain by placing global attention on important biomedical entities in several ways. We analyse the outputs of the 23 resulting models, and report patterns in the results related to the presence of additional global attention, number of training steps, and the input configuration.