3 citations · 6 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Decoding Memories: An Efficient Pipeline for Self-Consistency Hallucination Detection
Weizhi Gao, Xiaorui Liu, Feiyi Wang +2
Large language models (LLMs) have demonstrated impressive performance in both research and real-world applications, but they still struggle with hallucination. Existing hallucinati…
Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization
Weizhi Gao, Zhichao Hou, Junqi Yin +3
Diffusion models have emerged as powerful generative models, but their high computation cost in iterative sampling remains a significant bottleneck. In this work, we present an in-…
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,…