Papers by Liujia Yang

1 papers
MiniConGTS: A Near Ultimate Minimalist Contrastive Grid Tagging Scheme for Aspect Sentiment Triplet Extraction (2024.emnlp-main)

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Challenge: Existing approaches within the pretraining-finetuning paradigm tend to meticulously craft complex tagging schemes and classification heads, or incorporate external semantic enhancements to enhance performance.
Approach: They propose to integrate a minimalist tagging scheme and a novel token-level contrastive learning strategy to improve pretrained representations.
Outcome: The proposed framework achieves comparable or superior performance compared to state-of-the-art techniques while featuring a more compact design and reduced computational overhead.

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