most citedDefending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

12 citations · 16 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023★ 4 cited

ReMasker: Imputing Tabular Data with Masked Autoencoding

Tianyu Du, Luca Melis, Ting Wang

We present ReMasker, a new method of imputing missing values in tabular data by extending the masked autoencoding framework. Compared with prior work, ReMasker is both simple -- be…

cs.LG2023★ 12 cited

Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

Zhaohan Xi, Tianyu Du, Changjiang Li +5

Pre-trained language models (PLMs) have demonstrated remarkable performance as few-shot learners. However, their security risks under such settings are largely unexplored. In this…