9 citations · 27 across the 7 of their papers we have counts for
3 papers · 1 filter
Understanding Multi-Head Attention in Abstractive Summarization
Joris Baan, Maartje ter Hoeve, Marlies van der Wees +2
Attention mechanisms in deep learning architectures have often been used as a means of transparency and, as such, to shed light on the inner workings of the architectures. Recently…
Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?
Joris Baan, Maartje ter Hoeve, Marlies van der Wees +2
Learning algorithms become more powerful, often at the cost of increased complexity. In response, the demand for algorithms to be transparent is growing. In NLP tasks, attention di…
On the Realization of Compositionality in Neural Networks
Joris Baan, Jana Leible, Mitja Nikolaus +5
We present a detailed comparison of two types of sequence to sequence models trained to conduct a compositional task. The models are architecturally identical at inference time, bu…