333 citations · 395 across the 31 of their papers we have counts for
6 papers · 1 filter
VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
Ziyi Yin, Muchao Ye, Tianrong Zhang +6
Vision-Language (VL) pre-trained models have shown their superiority on many multimodal tasks. However, the adversarial robustness of such models has not been fully explored. Exist…
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…
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…
On the Security Risks of Knowledge Graph Reasoning
Zhaohan Xi, Tianyu Du, Changjiang Li +6
Knowledge graph reasoning (KGR) -- answering complex logical queries over large knowledge graphs -- represents an important artificial intelligence task, entailing a range of appli…
RNN-Guard: Certified Robustness Against Multi-frame Attacks for Recurrent Neural Networks
Yunruo Zhang, Tianyu Du, Shouling Ji +2
It is well-known that recurrent neural networks (RNNs), although widely used, are vulnerable to adversarial attacks including one-frame attacks and multi-frame attacks. Though a fe…
Torch-Choice: A PyTorch Package for Large-Scale Choice Modeling with Python
Tianyu Du, Ayush Kanodia, Susan Athey
The is an open-source library for flexible, fast choice modeling with Python and PyTorch. provides a data s…