17 citations · 27 across the 10 of their papers we have counts for
10 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…
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…
A Fine-grained Interpretability Evaluation Benchmark for Neural NLP
Lijie Wang, Yaozong Shen, Shuyuan Peng +7
While there is increasing concern about the interpretability of neural models, the evaluation of interpretability remains an open problem, due to the lack of proper evaluation data…
Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Loss
Kun Wu, Lijie Wang, Zhenghua Li +1
Grammar-based parsers have achieved high performance in the cross-domain text-to-SQL parsing task, but suffer from low decoding efficiency due to the much larger number of actions…
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
Lijie Wang, Hao Liu, Shuyuan Peng +5
While deep learning models have greatly improved the performance of most artificial intelligence tasks, they are often criticized to be untrustworthy due to the black-box problem.…
Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing
Kun Wu, Lijie Wang, Zhenghua Li +5
Data augmentation has attracted a lot of research attention in the deep learning era for its ability in alleviating data sparseness. The lack of labeled data for unseen evaluation…
A Practical Chinese Dependency Parser Based on A Large-scale Dataset
Shuai Zhang, Lijie Wang, Ke Sun +1
Dependency parsing is a longstanding natural language processing task, with its outputs crucial to various downstream tasks. Recently, neural network based (NN-based) dependency pa…
Image Aesthetics Prediction Using Multiple Patches Preserving the Original Aspect Ratio of Contents
Lijie Wang, Xueting Wang, Toshihiko Yamasaki
The spread of social networking services has created an increasing demand for selecting, editing, and generating impressive images. This trend increases the importance of evaluatin…