no code implementations • WMT (EMNLP) 2020 • Xiangpeng Wei, Ping Guo, Yunpeng Li, Xingsheng Zhang, Luxi Xing, Yue Hu
In this paper we introduce the systems IIE submitted for the WMT20 shared task on German-French news translation.
no code implementations • COLING 2022 • Yubing Ren, Yanan Cao, Fang Fang, Ping Guo, Zheng Lin, Wei Ma, Yi Liu
Transforming the large amounts of unstructured text on the Internet into structured event knowledge is a critical, yet unsolved goal of NLP, especially when addressing document-level text.
no code implementations • 13 Jan 2025 • Ping Guo, Cheng Gong, Xi Lin, Fei Liu, Zhichao Lu, Qingfu Zhang, Zhenkun Wang
Crafting adversarial examples is crucial for evaluating and enhancing the robustness of Deep Neural Networks (DNNs), presenting a challenge equivalent to maximizing a non-differentiable 0-1 loss function.
1 code implementation • 25 Dec 2024 • Ping Guo, Qingfu Zhang, Xi Lin
We propose a novel framework that utilizes LLMs in an evolutionary search methodology, augmented by a dynamic knowledge library that integrates and refines insights in an \textit{open-ended manner}.
no code implementations • 11 Oct 2024 • Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang
Algorithm Design (AD) is crucial for effective problem-solving across various domains.
no code implementations • 30 Mar 2024 • Ping Guo, Qingfu Zhang, Xi Lin
In many real-world applications, the Pareto Set (PS) of a continuous multiobjective optimization problem can be a piecewise continuous manifold.
no code implementations • 8 Mar 2024 • Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang
To address this gap, we propose a new metric termed adversarial hypervolume, assessing the robustness of deep learning models comprehensively over a range of perturbation intensities from a multi-objective optimization standpoint.
2 code implementations • 27 Jan 2024 • Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang
In the rapidly evolving field of machine learning, adversarial attacks present a significant challenge to model robustness and security.
no code implementations • 19 Jan 2024 • Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang
Black-box query-based attacks constitute significant threats to Machine Learning as a Service (MLaaS) systems since they can generate adversarial examples without accessing the target model's architecture and parameters.
1 code implementation • CVPR 2024 • Min Yang, Huan Gao, Ping Guo, LiMin Wang
To this end, we design effective cross-snippet propagation modules to gradually exchange short-term video information among different snippets from two levels.
1 code implementation • 3 Aug 2022 • Penglei Gao, Xi Yang, Rui Zhang, Ping Guo, John Y. Goulermas, Kaizhu Huang
While exogenous variables have a major impact on performance improvement in time series analysis, inter-series correlation and time dependence among them are rarely considered in the present continuous methods.
1 code implementation • 18 Feb 2022 • Yuqiang Xie, Yue Hu, Luxi Xing, Yunpeng Li, Wei Peng, Ping Guo
To address these two issues, we propose a novel Contrastive Learning framework for Story Ending Generation (CLSEG), which has two steps: multi-aspect sampling and story-specific contrastive learning.
no code implementations • 26 Oct 2021 • Ru Yang, Yang Li, Danielle Zeng, Ping Guo
StrainNet predicts the strain field directly from the image input without relying on the displacement prediction, which significantly improves the strain prediction accuracy.
no code implementations • ICCV 2021 • Zike Yan, Yuxin Tian, Xuesong Shi, Ping Guo, Peng Wang, Hongbin Zha
We introduce an experience replay approach to tackle an exemplary task of continual neural mapping: approximating a continuous signed distance function (SDF) from sequential depth images as a scene geometry representation.
no code implementations • 10 Mar 2021 • Ping Guo, Kaizhu Huang, Zenglin Xu
In this work, we generalize the reaction-diffusion equation in statistical physics, Schr\"odinger equation in quantum mechanics, Helmholtz equation in paraxial optics into the neural partial differential equations (NPDE), which can be considered as the fundamental equations in the field of artificial intelligence research.
1 code implementation • 1 Dec 2020 • Dongjiang Li, Jinyu Miao, Xuesong Shi, Yuxin Tian, Qiwei Long, Tianyu Cai, Ping Guo, Hongfei Yu, Wei Yang, Haosong Yue, Qi Wei, Fei Qiao
Experimental results show that the proposed RaP-Net trained with OpenLORIS-Location dataset achieves excellent performance in the feature matching task and significantly outperforms state-of-the-arts feature algorithms in indoor localization.
no code implementations • 31 May 2020 • Ping Guo, Qian Yin
Drawing on the idea that brain development is a Darwinian process of ``evolution + selection'' and the idea that the current state is a local equilibrium state of many bodies with self-organization and evolution processes driven by the temperature and gravity in our universe, in this work, we describe an artificial intelligence system called the ``Synergetic Learning Systems''.
no code implementations • 16 Feb 2020 • Jiali Xu, Qian Yin, Ping Guo, Xin Zheng
At the same time, the spectrum extraction results before and after calibration are compared, results show the characteristics of the extracted one-dimensional waveform are more close to an ideal optics system, and the PSF of the corrected object spectrum image estimated by the blind deconvolution method is nearly central symmetry, which indicates that our proposed method can significantly reduce the complexity of spectrum extraction and improve extraction accuracy.
no code implementations • 4 Nov 2019 • Lei Zhu, Qi She, Lidan Zhang, Ping Guo
The nonlocal-based blocks are designed for capturing long-range spatial-temporal dependencies in computer vision tasks.
no code implementations • 25 Sep 2019 • Lei Zhu, Qi She, Lidan Zhang, Ping Guo
The nonlocal network is designed for capturing long-range spatial-temporal dependencies in several computer vision tasks.
no code implementations • 24 Jul 2019 • Lidan Zhang, Qi She, Ping Guo
For the second issue, instead of modeling the uncertainty of the entire future as a whole, we utilize a temporal stochastic method for sequentially learning a prior model of uncertainty during social interactions.
no code implementations • 20 May 2018 • Ping Guo
In this paper, we briefly review the basic scheme of the pseudoinverse learning (PIL) algorithm and present some discussions on the PIL, as well as its variants.
no code implementations • 27 Nov 2017 • Ping Guo, Fuqing Duan, Pei Wang, Yao Yao, Qian Yin, Xin Xin
To address these problems, we proposed a framework which combines deep convolution generative adversarial network (DCGAN) with support vector machine (SVM) to deal with imbalance class problem and to improve pulsar identification accuracy.