63 citations · 147 across the 24 of their papers we have counts for
7 papers · 1 filter
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
Yixuan Su, Fangyu Liu, Zaiqiao Meng +4
Masked language models (MLMs) such as BERT and RoBERTa have revolutionized the field of Natural Language Understanding in the past few years. However, existing pre-trained MLMs oft…
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models
Zaiqiao Meng, Fangyu Liu, Ehsan Shareghi +3
Knowledge probing is crucial for understanding the knowledge transfer mechanism behind the pre-trained language models (PLMs). Despite the growing progress of probing knowledge for…
Mixture-of-Partitions: Infusing Large Biomedical Knowledge Graphs into BERT
Zaiqiao Meng, Fangyu Liu, Thomas Hikaru Clark +2
Infusing factual knowledge into pre-trained models is fundamental for many knowledge-intensive tasks. In this paper, we proposed Mixture-of-Partitions (MoP), an infusion approach t…
Few-Shot Table-to-Text Generation with Prototype Memory
Yixuan Su, Zaiqiao Meng, Simon Baker +1
Neural table-to-text generation models have achieved remarkable progress on an array of tasks. However, due to the data-hungry nature of neural models, their performances strongly…
Learning to Detect Few-Shot-Few-Clue Misinformation
Qiang Zhang, Hongbin Huang, Shangsong Liang +2
The quality of digital information on the web has been disquieting due to the lack of careful manual review. Consequently, a large volume of false textual information has been diss…
Graph Neural Pre-training for Enhancing Recommendations using Side Information
Zaiqiao Meng, Siwei Liu, Craig Macdonald +1
Leveraging the side information associated with entities (i.e. users and items) to enhance the performance of recommendation systems has been widely recognized as an important mode…
Learning Robust Recommenders through Cross-Model Agreement
Yu Wang, Xin Xin, Zaiqiao Meng +3
Learning from implicit feedback is one of the most common cases in the application of recommender systems. Generally speaking, interacted examples are considered as positive while…