3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 3 cited
SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases
Yanchen Liu, Jing Yan, Yan Chen +2
Recent studies reveal that various biases exist in different NLP tasks, and over-reliance on biases results in models' poor generalization ability and low adversarial robustness. T…
cs.CL2022
Less Learn Shortcut: Analyzing and Mitigating Learning of Spurious Feature-Label Correlation
Yanrui Du, Jing Yan, Yan Chen +6
Recent research has revealed that deep neural networks often take dataset biases as a shortcut to make decisions rather than understand tasks, leading to failures in real-world app…
cs.CL2021
DuQM: A Chinese Dataset of Linguistically Perturbed Natural Questions for Evaluating the Robustness of Question Matching Models
Hongyu Zhu, Yan Chen, Jing Yan +5
In this paper, we focus on studying robustness evaluation of Chinese question matching. Most of the previous work on analyzing robustness issue focus on just one or a few types of…