Arafat Sultan, Avi Sil, et al.
EMNLP 2022
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.
Arafat Sultan, Avi Sil, et al.
EMNLP 2022
Weichao Mao, Haoran Qiu, et al.
NeurIPS 2023
Pengfei He, Han Xu, et al.
ICLR 2024
Baifeng Shi, Judy Hoffman, et al.
NeurIPS 2020