Papers with sentiment-aware auxiliary tasks

1 papers
KESA: A Knowledge Enhanced Approach To Sentiment Analysis (2022.aacl-main)

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Challenge: Recent work on injecting sentiment knowledge into pre-trained language models, but it is difficult to integrate external knowledge into PLMs.
Approach: They propose two sentiment-aware auxiliary tasks to integrate sentiment knowledge into the objective of the downstream task.
Outcome: The proposed tasks outperform baselines and complement existing sentiment-enhanced models.

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