90 citations · 112 across the 12 of their papers we have counts for
5 papers · 2 filters
XPrompt: Exploring the Extreme of Prompt Tuning
Fang Ma, Chen Zhang, Lei Ren +5
Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gr…
CLOWER: A Pre-trained Language Model with Contrastive Learning over Word and Character Representations
Borun Chen, Hongyin Tang, Jiahao Bu +6
Pre-trained Language Models (PLMs) have achieved remarkable performance gains across numerous downstream tasks in natural language understanding. Various Chinese PLMs have been suc…
Structural Bias for Aspect Sentiment Triplet Extraction
Chen Zhang, Lei Ren, Fang Ma +3
Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly inco…
MiniDisc: Minimal Distillation Schedule for Language Model Compression
Chen Zhang, Yang Yang, Qifan Wang +4
Recent studies have uncovered that language model distillation is less effective when facing a large capacity gap between the teacher and the student, and introduced teacher assist…
Making Pretrained Language Models Good Long-tailed Learners
Chen Zhang, Lei Ren, Jingang Wang +2
Prompt-tuning has shown appealing performance in few-shot classification by virtue of its capability in effectively exploiting pre-trained knowledge. This motivates us to check the…