17 citations · 47 across the 10 of their papers we have counts for
14 papers
Advancing the Robustness of Large Language Models through Self-Denoised Smoothing
Jiabao Ji, Bairu Hou, Zhen Zhang +7
Although large language models (LLMs) have achieved significant success, their vulnerability to adversarial perturbations, including recent jailbreak attacks, has raised considerab…
Robust Mixture-of-Expert Training for Convolutional Neural Networks
Yihua Zhang, Ruisi Cai, Tianlong Chen +6
Sparsely-gated Mixture of Expert (MoE), an emerging deep model architecture, has demonstrated a great promise to enable high-accuracy and ultra-efficient model inference. Despite t…
Certified Robustness for Large Language Models with Self-Denoising
Zhen Zhang, Guanhua Zhang, Bairu Hou +5
Although large language models (LLMs) have achieved great success in vast real-world applications, their vulnerabilities towards noisy inputs have significantly limited their uses,…
Improving Diffusion Models for Scene Text Editing with Dual Encoders
Jiabao Ji, Guanhua Zhang, Zhaowen Wang +4
Scene text editing is a challenging task that involves modifying or inserting specified texts in an image while maintaining its natural and realistic appearance. Most previous appr…
Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models
Guanhua Zhang, Jiabao Ji, Yang Zhang +3
Image inpainting refers to the task of generating a complete, natural image based on a partially revealed reference image. Recently, many research interests have been focused on ad…
TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization
Bairu Hou, Jinghan Jia, Yihua Zhang +4
Robustness evaluation against adversarial examples has become increasingly important to unveil the trustworthiness of the prevailing deep models in natural language processing (NLP…