1 citations · 3 across the 5 of their papers we have counts for
5 papers
IBADR: an Iterative Bias-Aware Dataset Refinement Framework for Debiasing NLU models
Xiaoyue Wang, Xin Liu, Lijie Wang +3
As commonly-used methods for debiasing natural language understanding (NLU) models, dataset refinement approaches heavily rely on manual data analysis, and thus maybe unable to cov…
SkyMath: Technical Report
Liu Yang, Haihua Yang, Wenjun Cheng +14
Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning. In this work, we present Sk…
A Simple yet Effective Self-Debiasing Framework for Transformer Models
Xiaoyue Wang, Lijie Wang, Xin Liu +3
Current Transformer-based natural language understanding (NLU) models heavily rely on dataset biases, while failing to handle real-world out-of-distribution (OOD) instances. Many m…
SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Dataset
Saihao Huang, Lijie Wang, Zhenghua Li +6
As the first session-level Chinese dataset, CHASE contains two separate parts, i.e., 2,003 sessions manually constructed from scratch (CHASE-C), and 3,456 sessions translated from…
An Interpretability Evaluation Benchmark for Pre-trained Language Models
Yaozong Shen, Lijie Wang, Ying Chen +3
While pre-trained language models (LMs) have brought great improvements in many NLP tasks, there is increasing attention to explore capabilities of LMs and interpret their predicti…