Papers by Chenhao Meng
Train Once for All: A Transitional Approach for Efficient Aspect Sentiment Triplet Extraction (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches to extract aspects and opinions independently, optionally adding pairwise relations, often lead to error propagation and high time complexity. |
| Approach: | They propose a transition-based model that performs aspect and opinion extraction jointly and integrates contrastive-augmented optimization. |
| Outcome: | The proposed model outperforms previous models on two out of four datasets when trained on a single dataset. |