23 citations · 26 across the 4 of their papers we have counts for
4 papers · 1 filter
FOAL: Fine-grained Contrastive Learning for Cross-domain Aspect Sentiment Triplet Extraction
Ting Xu, Zhen Wu, Huiyun Yang +1
Aspect Sentiment Triplet Extraction (ASTE) has achieved promising results while relying on sufficient annotation data in a specific domain. However, it is infeasible to annotate da…
Measuring Your ASTE Models in The Wild: A Diversified Multi-domain Dataset For Aspect Sentiment Triplet Extraction
Ting Xu, Huiyun Yang, Zhen Wu +3
Aspect Sentiment Triplet Extraction (ASTE) is widely used in various applications. However, existing ASTE datasets are limited in their ability to represent real-world scenarios, h…
Enhancing Cross-lingual Transfer by Manifold Mixup
Huiyun Yang, Huadong Chen, Hao Zhou +1
Based on large-scale pre-trained multilingual representations, recent cross-lingual transfer methods have achieved impressive transfer performances. However, the performance of tar…
Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation
Huiyun Yang, Shujian Huang, Xinyu Dai +1
In sequence labeling, previous domain adaptation methods focus on the adaptation from the source domain to the entire target domain without considering the diversity of individual…