Search Results for author: Maartje ter Hoeve

Found 11 papers, 2 papers with code

Summarization with Graphical Elements

1 code implementation15 Apr 2022 Maartje ter Hoeve, Julia Kiseleva, Maarten de Rijke

Motivated from these two angles, we propose a new task: summarization with graphical elements, and we verify that these summaries are helpful for a critical mass of people.

Text Summarization

Towards Interactive Language Modeling

no code implementations14 Dec 2021 Maartje ter Hoeve, Evgeny Kharitonov, Dieuwke Hupkes, Emmanuel Dupoux

As a first contribution we present a road map in which we detail the steps that need to be taken towards interactive language modeling.

Language Acquisition Language Modelling

CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks

1 code implementation5 Feb 2021 Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke, Fabrizio Silvestri

In this work, we propose a method for generating CF explanations for GNNs: the minimal perturbation to the input (graph) data such that the prediction changes.

What Makes a Good and Useful Summary? Incorporating Users in Automatic Summarization Research

no code implementations14 Dec 2020 Maartje ter Hoeve, Julia Kiseleva, Maarten de Rijke

Motivated by our findings, we present ways to mitigate this mismatch in future research on automatic summarization: we propose research directions that impact the design, the development and the evaluation of automatically generated summaries.

Text Summarization

Conversations with Documents. An Exploration of Document-Centered Assistance

no code implementations27 Jan 2020 Maartje ter Hoeve, Robert Sim, Elnaz Nouri, Adam Fourney, Maarten de Rijke, Ryen W. White

Our contributions are three-fold: (1) We first present a survey to understand the space of document-centered assistance and the capabilities people expect in this scenario.

Understanding Multi-Head Attention in Abstractive Summarization

no code implementations10 Nov 2019 Joris Baan, Maartje ter Hoeve, Marlies van der Wees, Anne Schuth, Maarten de Rijke

Finally, we find that relative positions heads seem integral to summarization performance and persistently remain after pruning.

Abstractive Text Summarization Machine Translation +1

Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?

no code implementations1 Jul 2019 Joris Baan, Maartje ter Hoeve, Marlies van der Wees, Anne Schuth, Maarten de Rijke

We investigate whether distributions calculated by different attention heads in a transformer architecture can be used to improve transparency in the task of abstractive summarization.

Abstractive Text Summarization

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