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20202023
most citedA Practical Chinese Dependency Parser Based on A Large-scale Dataset

17 citations · 22 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2023

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…

cs.CL20231 cited

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…

cs.CL2022

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…

cs.CL20213 cited

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.…

cs.CL202017 cited

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…