most citedAPAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning

1 citations · 2 across the 3 of their papers we have counts for

collaborators
Showing cs.CLShow all

2 papers · 1 filter

cs.CL2023

Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models

Jiang Zhang, Qiong Wu, Yiming Xu +3

Toxic content detection is crucial for online services to remove inappropriate content that violates community standards. To automate the detection process, prior works have propos…

cs.CL2023★ 1 cited

APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning

Sunyi Chi, Bo Dong, Yiming Xu +2

Practical natural language processing (NLP) tasks are commonly long-tailed with noisy labels. Those problems challenge the generalization and robustness of complex models such as D…