APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning

Yang Gao, Christian M. Meyer, Iryna Gurevych

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Abstract
We propose a method to perform automatic document summarisation without using reference summaries. Instead, our method interactively learns from users’ preferences. The merit of preference-based interactive summarisation is that preferences are easier for users to provide than reference summaries. Existing preference-based interactive learning methods suffer from high sample complexity, i.e. they need to interact with the oracle for many rounds in order to converge. In this work, we propose a new objective function, which enables us to leverage active learning, preference learning and reinforcement learning techniques in order to reduce the sample complexity. Both simulation and real-user experiments suggest that our method significantly advances the state of the art. Our source code is freely available at https://github.com/UKPLab/emnlp2018-april.
Anthology ID:
D18-1445
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Month:
October-November
Year:
2018
Address:
Brussels, Belgium
Editors:
Ellen Riloff, David Chiang, Julia Hockenmaier, Jun’ichi Tsujii
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
4120–4130
Language:
URL:
https://aclanthology.org/D18-1445
DOI:
10.18653/v1/D18-1445
Bibkey:
Cite (ACL):
Yang Gao, Christian M. Meyer, and Iryna Gurevych. 2018. APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 4120–4130, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning (Gao et al., EMNLP 2018)
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PDF:
https://preview.aclanthology.org/teach-a-man-to-fish/D18-1445.pdf
Attachment:
 D18-1445.Attachment.zip
Code
 UKPLab/emnlp2018-april
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