6 citations · 10 across the 7 of their papers we have counts for
4 papers · 1 filter
PATS: Sensitivity-aware Noisy Learning for Pretrained Language Models
Yupeng Zhang, Hongzhi Zhang, Sirui Wang +2
A wide range of NLP tasks benefit from the fine-tuning of pretrained language models (PLMs). However, a number of redundant parameters which contribute less to the downstream task…
Improving Semantic Matching through Dependency-Enhanced Pre-trained Model with Adaptive Fusion
Jian Song, Di Liang, Rumei Li +5
Transformer-based pre-trained models like BERT have achieved great progress on Semantic Sentence Matching. Meanwhile, dependency prior knowledge has also shown general benefits in…
DABERT: Dual Attention Enhanced BERT for Semantic Matching
Sirui Wang, Di Liang, Jian Song +2
Transformer-based pre-trained language models such as BERT have achieved remarkable results in Semantic Sentence Matching. However, existing models still suffer from insufficient a…
Let Me Check the Examples: Enhancing Demonstration Learning via Explicit Imitation
Sirui Wang, Kaiwen Wei, Hongzhi Zhang +2
Demonstration learning aims to guide the prompt prediction via providing answered demonstrations in the few shot settings. Despite achieving promising results, existing work only c…