1 code implementation • 24 Oct 2023 • Shiao Meng, Xuming Hu, Aiwei Liu, Shu'ang Li, Fukun Ma, Yawen Yang, Lijie Wen
However, existing works often struggle to obtain class prototypes with accurate relational semantics: 1) To build prototype for a target relation type, they aggregate the representations of all entity pairs holding that relation, while these entity pairs may also hold other relations, thus disturbing the prototype.
no code implementations • 29 May 2023 • Aiwei Liu, Wei Liu, Xuming Hu, Shuang Li, Fukun Ma, Yawen Yang, Lijie Wen
Based on these observations, we propose a method named \texttt{p-align} to improve the compositional generalization of Text-to-SQL models.
1 code implementation • 22 May 2023 • Shuang Li, Xuming Hu, Aiwei Liu, Yawen Yang, Fukun Ma, Philip S. Yu, Lijie Wen
In this paper, we propose a novel Soft prompt learning framework with the Multilingual Verbalizer (SoftMV) for XNLI.
Cross-Lingual Natural Language Inference Cross-Lingual Transfer
no code implementations • 12 May 2023 • Yawen Yang, Xuming Hu, Fukun Ma, Shu'ang Li, Aiwei Liu, Lijie Wen, Philip S. Yu
Existing works for nested NER ignore the recognition order and boundary position relation of nested entities.
1 code implementation • 31 Oct 2022 • Aiwei Liu, Honghai Yu, Xuming Hu, Shu'ang Li, Li Lin, Fukun Ma, Yawen Yang, Lijie Wen
We propose the first character-level white-box adversarial attack method against transformer models.
1 code implementation • Findings (EMNLP) 2021 • Xuming Hu, Chenwei Zhang, Fukun Ma, Chenyao Liu, Lijie Wen, Philip S. Yu
To alleviate human efforts from obtaining large-scale annotations, Semi-Supervised Relation Extraction methods aim to leverage unlabeled data in addition to learning from limited samples.