Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

Md Faisal Mahbub Chowdhury; Gaetano Rossiello; Michael Glass; Nandana Mihindukulasooriya; Alfio Gliozzo

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arXiv · 2201.05302

Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

Md Faisal Mahbub Chowdhury·Gaetano Rossiello·Michael Glass·Nandana Mihindukulasooriya·Alfio Gliozzo

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Abstract

In recent years, a number of keyphrase generation (KPG) approaches were proposed consisting of complex model architectures, dedicated training paradigms and decoding strategies. In this work, we opt for simplicity and show how a commonly used seq2seq language model, BART, can be easily adapted to generate keyphrases from the text in a single batch computation using a simple training procedure. Empirical results on five benchmarks show that our approach is as good as the existing state-of-the-art KPG systems, but using a much simpler and easy to deploy framework.

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Md Faisal Mahbub Chowdhury, Gaetano Rossiello, Michael Glass, Nandana Mihindukulasooriya, Alfio Gliozzo. 2022-01-14. Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation. https://arxiv.org/abs/2201.05302

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