HydraSum: Disentangling Stylistic Features in Text Summarization… (Paper Review/Described)

Author(s): Ala Alam Falaki

Originally published on Towards AI.

Training

Is it possible to train a model with transformer architecture to learn generating summaries with different styles?

Figure 1. The multi-decoder architecture scheme. (Image from [1])

While it’s true that deep learning (specifically transformer architecture) keeps pushing the SOTA scores, they have a kind of significant shortcoming. No, I am not talking about their memory usage! We know how to train them, but we do not have any control over what they will learn. For instance, it is a missing feature in Text Summarization models to control the output to set a length or style. Let’s see if we can do anything… Read the full blog for free on Medium.

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Published via Towards AI