In this work, we propose a new objective function, which enables us to leverage active learning, preference learning and reinforcement learning techniques in ...
Aug 29, 2018 · Abstract:We propose a method to perform automatic document summarisation without using reference summaries.
A new objective function is proposed, which enables the method to perform automatic document summarisation without using reference summaries to leverage ...
APRIL is an interactive document summarisation framework. Instead of learning from reference summaries, APRIL interacts with the users/oracles to obtain ...
In this paper, preference-based reinforcement learning is combined with active ranking in order to decrease the number of ranking queries to the expert ...
Aug 5, 2024 · APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning. EMNLP 2018: 4120-4130. [c18].
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APRIL uses active learning to query the user, preference learning to learn a summary ranking function from the preferences, and neural Reinforcement learning to ...
APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning. Y Gao, CM Meyer, I Gurevych.
Meyer, Iryna Gurevych. APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning. Proceedings of 2018 ...
APRIL: Interactively Learning to Summarise by Combining Active Preference Learning and Reinforcement Learning. In: Proceedings of the 2018 Conference on ...