Papers by Sang-Rak Lee
SentiCSE: A Sentiment-aware Contrastive Sentence Embedding Framework with Sentiment-guided Textual Similarity (2024.lrec-main)
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| Challenge: | Sentiment-aware pre-trained language models (PLMs) demonstrate impressive results in downstream sentiment analysis tasks, but they neglect to evaluate the quality of constructed sentiment representations. |
| Approach: | They propose a new metric for evaluating the quality of sentiment representations that is based on the degree of equivalence in sentiment polarity between two sentences. |
| Outcome: | The proposed framework outperforms the existing sentiment-aware models in sentiment analysis tasks. |