4 citations · 6 across the 3 of their papers we have counts for
6 papers
Understanding Silent Data Corruption in LLM Training
Jeffrey Ma, Hengzhi Pei, Leonard Lausen +1
As the scale of training large language models (LLMs) increases, one emergent failure is silent data corruption (SDC), where hardware produces incorrect computations without explic…
TextGuard: Provable Defense against Backdoor Attacks on Text Classification
Hengzhi Pei, Jinyuan Jia, Wenbo Guo +2
Backdoor attacks have become a major security threat for deploying machine learning models in security-critical applications. Existing research endeavors have proposed many defense…
Reinforcement-Learning based Portfolio Management with Augmented Asset Movement Prediction States
Yunan Ye, Hengzhi Pei, Boxin Wang +4
Portfolio management (PM) is a fundamental financial planning task that aims to achieve investment goals such as maximal profits or minimal risks. Its decision process involves con…
T3: Tree-Autoencoder Constrained Adversarial Text Generation for Targeted Attack
Boxin Wang, Hengzhi Pei, Boyuan Pan +3
Adversarial attacks against natural language processing systems, which perform seemingly innocuous modifications to inputs, can induce arbitrary mistakes to the target models. Thou…
The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks
Yuheng Zhang, Ruoxi Jia, Hengzhi Pei +3
This paper studies model-inversion attacks, in which the access to a model is abused to infer information about the training data. Since its first introduction, such attacks have r…
A Concise Model for Multi-Criteria Chinese Word Segmentation with Transformer Encoder
Xipeng Qiu, Hengzhi Pei, Hang Yan +1
Multi-criteria Chinese word segmentation (MCCWS) aims to exploit the relations among the multiple heterogeneous segmentation criteria and further improve the performance of each si…