activity
20122022
most citedTowards Understanding and Boosting Adversarial Transferability from a Distribution Perspective

74 citations · 119 across the 8 of their papers we have counts for

collaborators

11 papers

cs.CV2022

Rethinking Out-of-Distribution Detection From a Human-Centric Perspective

Yao Zhu, Yuefeng Chen, Xiaodan Li +6

Out-Of-Distribution (OOD) detection has received broad attention over the years, aiming to ensure the reliability and safety of deep neural networks (DNNs) in real-world scenarios…

cs.CV202274 cited

Towards Understanding and Boosting Adversarial Transferability from a Distribution Perspective

Yao Zhu, Yuefeng Chen, Xiaodan Li +6

Transferable adversarial attacks against Deep neural networks (DNNs) have received broad attention in recent years. An adversarial example can be crafted by a surrogate model and t…

cs.CL2022

CREATER: CTR-driven Advertising Text Generation with Controlled Pre-Training and Contrastive Fine-Tuning

Penghui Wei, Xuanhua Yang, Shaoguo Liu +2

This paper focuses on automatically generating the text of an ad, and the goal is that the generated text can capture user interest for achieving higher click-through rate (CTR). W…

cs.GR2022

Dressi: A Hardware-Agnostic Differentiable Renderer with Reactive Shader Packing and Soft Rasterization

Yusuke Takimoto, Hiroyuki Sato, Hikari Takehara +6

Differentiable rendering (DR) enables various computer graphics and computer vision applications through gradient-based optimization with derivatives of the rendering equation. Mos…

cs.IR2022

UKD: Debiasing Conversion Rate Estimation via Uncertainty-regularized Knowledge Distillation

Zixuan Xu, Penghui Wei, Weimin Zhang +3

In online advertising, conventional post-click conversion rate (CVR) estimation models are trained using clicked samples. However, during online serving the models need to estimate…

cs.CL2021

Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training

Bo Zheng, Li Dong, Shaohan Huang +5

Compared to monolingual models, cross-lingual models usually require a more expressive vocabulary to represent all languages adequately. We find that many languages are under-repre…