3 citations · 6 across the 5 of their papers we have counts for
5 papers
Understanding Long Programming Languages with Structure-Aware Sparse Attention
Tingting Liu, Chengyu Wang, Cen Chen +2
Programming-based Pre-trained Language Models (PPLMs) such as CodeBERT have achieved great success in many downstream code-related tasks. Since the memory and computational complex…
Towards Unified Prompt Tuning for Few-shot Text Classification
Jianing Wang, Chengyu Wang, Fuli Luo +6
Prompt-based fine-tuning has boosted the performance of Pre-trained Language Models (PLMs) on few-shot text classification by employing task-specific prompts. Yet, PLMs are unfamil…
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering
Jianing Wang, Chengyu Wang, Minghui Qiu +4
Extractive Question Answering (EQA) is one of the most important tasks in Machine Reading Comprehension (MRC), which can be solved by fine-tuning the span selecting heads of Pre-tr…
Making Pre-trained Language Models End-to-end Few-shot Learners with Contrastive Prompt Tuning
Ziyun Xu, Chengyu Wang, Minghui Qiu +4
Pre-trained Language Models (PLMs) have achieved remarkable performance for various language understanding tasks in IR systems, which require the fine-tuning process based on label…
HiCLRE: A Hierarchical Contrastive Learning Framework for Distantly Supervised Relation Extraction
Dongyang Li, Taolin Zhang, Nan Hu +2
Distant supervision assumes that any sentence containing the same entity pairs reflects identical relationships. Previous works of distantly supervised relation extraction (DSRE) t…