Sparse Fuzzy Attention for Structured Sentiment Analysis
- URL: http://arxiv.org/abs/2109.06719v2
- Date: Wed, 15 Sep 2021 08:38:33 GMT
- Title: Sparse Fuzzy Attention for Structured Sentiment Analysis
- Authors: Letain Peng, Zuchao Li and Hai Zhao
- Abstract summary: We propose a sparse and fuzzy attention scorer with pooling layers which improves performance and sets the new state-of-the-art on structured sentiment analysis.
We further explore the parsing modeling on structured sentiment analysis with second-order parsing and introduce a novel sparse second-order edge building procedure that leads to significant improvement in parsing performance.
- Score: 48.69930912510414
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Attention scorers have achieved success in parsing tasks like semantic and
syntactic dependency parsing. However, in tasks modeled into parsing, like
structured sentiment analysis, "dependency edges" are very sparse which hinders
parser performance. Thus we propose a sparse and fuzzy attention scorer with
pooling layers which improves parser performance and sets the new
state-of-the-art on structured sentiment analysis. We further explore the
parsing modeling on structured sentiment analysis with second-order parsing and
introduce a novel sparse second-order edge building procedure that leads to
significant improvement in parsing performance.
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