17 citations · 26 across the 14 of their papers we have counts for
9 papers · 1 filter
PowerMLP: An Efficient Version of KAN
Ruichen Qiu, Yibo Miao, Shiwen Wang +3
The Kolmogorov-Arnold Network (KAN) is a new network architecture known for its high accuracy in several tasks such as function fitting and PDE solving. The superior expressive cap…
Generalizability of Memorization Neural Networks
Lijia Yu, Xiao-Shan Gao, Lijun Zhang +1
The neural network memorization problem is to study the expressive power of neural networks to interpolate a finite dataset. Although memorization is widely believed to have a clos…
T2VSafetyBench: Evaluating the Safety of Text-to-Video Generative Models
Yibo Miao, Yifan Zhu, Yinpeng Dong +3
The recent development of Sora leads to a new era in text-to-video (T2V) generation. Along with this comes the rising concern about its security risks. The generated videos may con…
Toward Availability Attacks in 3D Point Clouds
Yifan Zhu, Yibo Miao, Yinpeng Dong +1
Despite the great progress of 3D vision, data privacy and security issues in 3D deep learning are not explored systematically. In the domain of 2D images, many availability attacks…
Generalization Bound and New Algorithm for Clean-Label Backdoor Attack
Lijia Yu, Shuang Liu, Yibo Miao +2
The generalization bound is a crucial theoretical tool for assessing the generalizability of learning methods and there exist vast literatures on generalizability of normal learnin…
AdaMoE: Token-Adaptive Routing with Null Experts for Mixture-of-Experts Language Models
Zihao Zeng, Yibo Miao, Hongcheng Gao +2
Mixture of experts (MoE) has become the standard for constructing production-level large language models (LLMs) due to its promise to boost model capacity without causing significa…
3D-Properties: Identifying Challenges in DPO and Charting a Path Forward
Yuzi Yan, Yibo Miao, Jialian Li +4
Aligning large language models (LLMs) with human preferences has gained significant attention, with Proximal Policy Optimization (PPO) as a standard yet computationally expensive m…
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng, Yibo Miao, Yinpeng Dong +3
This paper studies the challenging black-box adversarial attack that aims to generate adversarial examples against a black-box model by only using output feedback of the model to i…
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification
Yibo Miao, Yu Lei, Feng Zhou +1
Low-shot image classification is a fundamental task in computer vision, and the emergence of large-scale vision-language models such as CLIP has greatly advanced the forefront of r…