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            <title>Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing</title>
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    <abstract>Aspect category sentiment analysis has attracted increasing research attention. The dominant methods make use of pre-trained language models by learning effective aspect category-specific representations, and adding specific output layers to its pre-trained representation. We consider a more direct way of making use of pre-trained language models, by casting the ACSA tasks into natural language generation tasks, using natural language sentences to represent the output. Our method allows more direct use of pre-trained knowledge in seq2seq language models by directly following the task setting during pre-training. Experiments on several benchmarks show that our method gives the best reported results, having large advantages in few-shot and zero-shot settings.</abstract>
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    <identifier type="doi">10.18653/v1/2021.emnlp-main.361</identifier>
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%0 Conference Proceedings
%T Solving Aspect Category Sentiment Analysis as a Text Generation Task
%A Liu, Jian
%A Teng, Zhiyang
%A Cui, Leyang
%A Liu, Hanmeng
%A Zhang, Yue
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F liu-etal-2021-solving
%X Aspect category sentiment analysis has attracted increasing research attention. The dominant methods make use of pre-trained language models by learning effective aspect category-specific representations, and adding specific output layers to its pre-trained representation. We consider a more direct way of making use of pre-trained language models, by casting the ACSA tasks into natural language generation tasks, using natural language sentences to represent the output. Our method allows more direct use of pre-trained knowledge in seq2seq language models by directly following the task setting during pre-training. Experiments on several benchmarks show that our method gives the best reported results, having large advantages in few-shot and zero-shot settings.
%R 10.18653/v1/2021.emnlp-main.361
%U https://aclanthology.org/2021.emnlp-main.361
%U https://doi.org/10.18653/v1/2021.emnlp-main.361
%P 4406-4416

Markdown (Informal)

[Solving Aspect Category Sentiment Analysis as a Text Generation Task](https://aclanthology.org/2021.emnlp-main.361) (Liu et al., EMNLP 2021)

• Solving Aspect Category Sentiment Analysis as a Text Generation Task (Liu et al., EMNLP 2021)

ACL

• Jian Liu, Zhiyang Teng, Leyang Cui, Hanmeng Liu, and Yue Zhang. 2021. Solving Aspect Category Sentiment Analysis as a Text Generation Task. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 4406–4416, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.