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20232026
most citedRobust Graph Neural Networks via Unbiased Aggregation

3 citations · 6 across the 10 of their papers we have counts for

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7 papers · 1 filter

cs.LG2026

Towards One-for-All Robustness Across a Continuum of Threat Levels

Zhichao Hou, Xiaorui Liu

Adversarially robust models often overfit to a specific attack budget, necessitating multiple specialized models for diverse and dynamic adversarial environments, a strategy that b…

cs.LG2025

Fine-Grained Iterative Adversarial Attacks with Limited Computation Budget

Zhichao Hou, Weizhi Gao, Xiaorui Liu

This work tackles a critical challenge in AI safety research under limited compute: given a fixed computation budget, how can one maximize the strength of iterative adversarial att…

cs.LG2025

Boosting Adversarial Robustness and Generalization with Dictionary Structure

Zhichao Hou, Weizhi Gao, Hamid Krim +2

This work investigates a novel approach to boost adversarial robustness and generalization by incorporating structural prior into the design of deep learning models. Specifically,…

cs.LG2024★ 1 cited

Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing

Weizhi Gao, Zhichao Hou, Han Xu +1

Implicit models such as Deep Equilibrium Models (DEQs) have emerged as promising alternative approaches for building deep neural networks. Their certified robustness has gained inc…

cs.LG2024★ 2 cited

ProTransformer: Robustify Transformers via Plug-and-Play Paradigm

Zhichao Hou, Weizhi Gao, Yuchen Shen +2

Transformer-based architectures have dominated various areas of machine learning in recent years. In this paper, we introduce a novel robust attention mechanism designed to enhance…

cs.LG2024

Robustness Reprogramming for Representation Learning

Zhichao Hou, MohamadAli Torkamani, Hamid Krim +1

This work tackles an intriguing and fundamental open challenge in representation learning: Given a well-trained deep learning model, can it be reprogrammed to enhance its robustnes…

cs.LG2023★ 3 cited

Robust Graph Neural Networks via Unbiased Aggregation

Zhichao Hou, Ruiqi Feng, Tyler Derr +1

The adversarial robustness of Graph Neural Networks (GNNs) has been questioned due to the false sense of security uncovered by strong adaptive attacks despite the existence of nume…