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Found 6 papers, 2 papers with code
VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding
The success of Natural Language Understanding (NLU) benchmarks in various languages, such as GLUE for English, CLUE for Chinese, KLUE for Korean, and IndoNLU for Indonesian, has facilitated the evaluation of new NLU models across a wide range of tasks.
AGent: A Novel Pipeline for Automatically Creating Unanswerable Questions
In this paper, we demonstrate the usefulness of this AGent pipeline by creating two sets of unanswerable questions from answerable questions in SQuAD and HotpotQA.
Single-Sentence Reader: A Novel Approach for Addressing Answer Position Bias
Machine Reading Comprehension (MRC) models tend to take advantage of spurious correlations (also known as dataset bias or annotation artifacts in the research community).
Revealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehension
From the analysis results, we suggest new directions for developing Vietnamese language models.
The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models
Pretrained language models have achieved super-human performances on many Machine Reading Comprehension (MRC) benchmarks.
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension
To address the weakness, we provide the research community with a benchmark dataset named UIT-ViQuAD 2. 0 for evaluating the MRC task and question answering systems for the Vietnamese language.
