Papers by Songhua Yang

1 papers
FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysis (2024.lrec-main)

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Challenge: Existing methods for aspect-based sentiment analysis are limited and integrating with existing techniques is difficult.
Approach: They propose a framework that utilizes in-context learning as a feature-aware mechanism that facilitates adaptive learning in multi-domain ABSA tasks.
Outcome: The proposed framework achieves significant performance improvements in multiple domains compared to baselines, increasing F1 by 2.07% on average.

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