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        <title>Less is More: Attention Supervision with Counterfactuals for Text Classification</title>
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        <namePart type="given">Seungtaek</namePart>
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        <namePart type="given">Seung-won</namePart>
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    <abstract>We aim to leverage human and machine intelligence together for attention supervision. Specifically, we show that human annotation cost can be kept reasonably low, while its quality can be enhanced by machine self-supervision. Specifically, for this goal, we explore the advantage of counterfactual reasoning, over associative reasoning typically used in attention supervision. Our empirical results show that this machine-augmented human attention supervision is more effective than existing methods requiring a higher annotation cost, in text classification tasks, including sentiment analysis and news categorization.</abstract>
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%0 Conference Proceedings
%T Less is More: Attention Supervision with Counterfactuals for Text Classification
%A Choi, Seungtaek
%A Park, Haeju
%A Yeo, Jinyoung
%A Hwang, Seung-won
%Y Webber, Bonnie
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F choi-etal-2020-less
%X We aim to leverage human and machine intelligence together for attention supervision. Specifically, we show that human annotation cost can be kept reasonably low, while its quality can be enhanced by machine self-supervision. Specifically, for this goal, we explore the advantage of counterfactual reasoning, over associative reasoning typically used in attention supervision. Our empirical results show that this machine-augmented human attention supervision is more effective than existing methods requiring a higher annotation cost, in text classification tasks, including sentiment analysis and news categorization.
%R 10.18653/v1/2020.emnlp-main.543
%U https://aclanthology.org/2020.emnlp-main.543/
%U https://doi.org/10.18653/v1/2020.emnlp-main.543
%P 6695-6704

Markdown (Informal)

[Less is More: Attention Supervision with Counterfactuals for Text Classification](https://aclanthology.org/2020.emnlp-main.543/) (Choi et al., EMNLP 2020)

• Less is More: Attention Supervision with Counterfactuals for Text Classification (Choi et al., EMNLP 2020)

ACL

• Seungtaek Choi, Haeju Park, Jinyoung Yeo, and Seung-won Hwang. 2020. Less is More: Attention Supervision with Counterfactuals for Text Classification. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6695–6704, Online. Association for Computational Linguistics.