1 code implementation • 9 Nov 2023 • Licheng Wen, Xuemeng Yang, Daocheng Fu, XiaoFeng Wang, Pinlong Cai, Xin Li, Tao Ma, Yingxuan Li, Linran Xu, Dengke Shang, Zheng Zhu, Shaoyan Sun, Yeqi Bai, Xinyu Cai, Min Dou, Shuanglu Hu, Botian Shi, Yu Qiao
This has been a significant bottleneck, particularly in the development of common sense reasoning and nuanced scene understanding necessary for safe and reliable autonomous driving.
no code implementations • 24 Oct 2023 • Xiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan, Lei Jin, ZiHao Wang, Liya Su, XiaoFeng Wang, Haixu Tang
In the attack, one can construct a PII association task, whereby an LLM is fine-tuned using a minuscule PII dataset, to potentially reinstate and reveal concealed PIIs.
no code implementations • 28 Sep 2023 • Xiaotian Zhou, Qian Wang, XiaoFeng Wang, Haixu Tang, Xiaozhong Liu
Large language models (LLMs) have demonstrated human-level performance on a vast spectrum of natural language tasks.
no code implementations • 26 Sep 2023 • Alphan Sahin, XiaoFeng Wang
In this study, we propose a non-coherent over-the-air computation (OAC) scheme to calculate the majority vote (MV) reliably in fading channels.
no code implementations • 18 Sep 2023 • XiaoFeng Wang, Zheng Zhu, Guan Huang, Xinze Chen, Jiagang Zhu, Jiwen Lu
The established world model holds immense potential for the generation of high-quality driving videos, and driving policies for safe maneuvering.
no code implementations • 31 Jul 2023 • Xin Zhang, Yuqi Song, Fei Zuo, XiaoFeng Wang
In this work, we address the issue of label imbalance and investigate how to train classifiers using partial labels in large labeling spaces.
no code implementations • ICCV 2023 • Rabab Abdelfattah, Qing Guo, Xiaoguang Li, XiaoFeng Wang, Song Wang
Using the aggregated similarity scores as the initial pseudo labels at the training stage, we propose an optimization framework to train the parameters of the classification network and refine pseudo labels for unobserved labels.
no code implementations • 22 Apr 2023 • Zilong Lin, Zhengyi Li, Xiaojing Liao, XiaoFeng Wang, Xiaozhong Liu
As a prominent instance of vandalism edits, Wiki search poisoning for illicit promotion is a cybercrime in which the adversary aims at editing Wiki articles to promote illicit businesses through Wiki search results of relevant queries.
no code implementations • 3 Apr 2023 • Xin Zhang, Yuqi Song, XiaoFeng Wang, Fei Zuo
However, concerns have been raised with respect to the trustworthiness of these models: The standard testing method evaluates the performance of a model on a test set, while low-quality and insufficient test sets can lead to unreliable evaluation results, which can have unforeseeable consequences.
no code implementations • 16 Mar 2023 • Mengxin Zheng, Jiaqi Xue, ZiHao Wang, Xun Chen, Qian Lou, Lei Jiang, XiaoFeng Wang
We evaluated SSL-Cleanse on various datasets using 1200 encoders, achieving an average detection success rate of 82. 2% on ImageNet-100.
1 code implementation • ICCV 2023 • XiaoFeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang, Yi Wei, Xu Chi, Yun Ye, Dalong Du, Jiwen Lu, Xingang Wang
Towards a comprehensive benchmarking of surrounding perception algorithms, we propose OpenOccupancy, which is the first surrounding semantic occupancy perception benchmark.
no code implementations • 30 Jan 2023 • Xintao Chu, Jianping Liu, Jian Wang, XiaoFeng Wang, Yingfei Wang, Meng Wang, Xunxun Gu
As the number of open and shared scientific datasets on the Internet increases under the open science movement, efficiently retrieving these datasets is a crucial task in information retrieval (IR) research.
no code implementations • 29 Jan 2023 • Rui Zhu, Di Tang, Siyuan Tang, Guanhong Tao, Shiqing Ma, XiaoFeng Wang, Haixu Tang
Finally, we perform both theoretical and experimental analysis, showing that the GRASP enhancement does not reduce the effectiveness of the stealthy attacks against the backdoor detection methods based on weight analysis, as well as other backdoor mitigation methods without using detection.
no code implementations • 19 Jan 2023 • Yingfei Wang, Jianping Liu, Jian Wang, XiaoFeng Wang, Meng Wang, Xintao Chu
In this paper, We use Transformer as the backbone network of feature extraction, add filter layer innovatively, and propose a new Filter-Enhanced Transformer Click Model (FE-TCM) for web search.
1 code implementation • CVPR 2023 • XiaoFeng Wang, Zheng Zhu, Yunpeng Zhang, Guan Huang, Yun Ye, Wenbo Xu, Ziwei Chen, Xingang Wang
To mitigate the problem, we propose the Autonomous-driving StreAming Perception (ASAP) benchmark, which is the first benchmark to evaluate the online performance of vision-centric perception in autonomous driving.
no code implementations • 9 Dec 2022 • Rui Zhu, Di Tang, Siyuan Tang, XiaoFeng Wang, Haixu Tang
Our idea is to retrain a given DNN model on randomly labeled clean data, to induce a CF on the model, leading to a sudden forget on both primary and backdoor tasks; then we recover the primary task by retraining the randomized model on correctly labeled clean data.
no code implementations • 24 Oct 2022 • Xin Zhang, Rabab Abdelfattah, Yuqi Song, Samuel A. Dauchert, XiaoFeng Wang
Depth information is the foundation of perception, essential for autonomous driving, robotics, and other source-constrained applications.
no code implementations • 24 Oct 2022 • Xin Zhang, Rabab Abdelfattah, Yuqi Song, XiaoFeng Wang
Through comprehensive experiments on three large-scale multi-label image datasets, i. e. MS-COCO, NUS-WIDE, and Pascal VOC12, we show that our method can handle the imbalance between positive labels and negative labels, while still outperforming existing missing-label learning approaches in most cases, and in some cases even approaches with fully labeled datasets.
no code implementations • 20 Oct 2022 • Rabab Abdelfattah, Xin Zhang, Mostafa M. Fouda, XiaoFeng Wang, Song Wang
To effectively address partial-label classification, this paper proposes an end-to-end Generic Game-theoretic Network (G2NetPL) for partial-label learning, which can be applied to most partial-label settings, including a very challenging, but annotation-efficient case where only a subset of the training images are labeled, each with only one positive label, while the rest of the training images remain unlabeled.
Multi-Label Classification
Multi-Label Image Classification
+2
no code implementations • 12 Oct 2022 • Di Tang, Rui Zhu, XiaoFeng Wang, Haixu Tang, Yi Chen
With extensive studies on backdoor attack and detection, still fundamental questions are left unanswered regarding the limits in the adversary's capability to attack and the defender's capability to detect.
1 code implementation • 14 Sep 2022 • Jiawei Liu, Yangyang Kang, Di Tang, Kaisong Song, Changlong Sun, XiaoFeng Wang, Wei Lu, Xiaozhong Liu
In this study, we propose an imitation adversarial attack on black-box neural passage ranking models.
no code implementations • 24 Aug 2022 • Yuanliang Zhang, XiaoFeng Wang, Jinxin Hu, Ke Gao, Chenyi Lei, Fei Fang
we summarize three practical challenges which are not well solved for multi-scenario modeling: (1) Lacking of fine-grained and decoupled information transfer controls among multiple scenarios.
no code implementations • 22 Aug 2022 • Rabab Abdelfattah, Xin Zhang, Zhenyao Wu, Xinyi Wu, XiaoFeng Wang, Song Wang
A special case is to annotate only one positive label in each training image.
Multi-Label Classification
Multi-Label Image Classification
+1
1 code implementation • 19 Aug 2022 • XiaoFeng Wang, Zheng Zhu, Guan Huang, Xu Chi, Yun Ye, Ziwei Chen, Xingang Wang
In contrast, multi-frame depth estimation methods improve the depth accuracy thanks to the success of Multi-View Stereo (MVS), which directly makes use of geometric constraints.
1 code implementation • 15 Apr 2022 • XiaoFeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang, Xu Chi, Yijia He, Xingang Wang
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
1 code implementation • 14 Apr 2022 • Rabab Abdelfattah, XiaoFeng Wang, Song Wang
Accurate segmentation of power lines in various aerial images is very important for UAV flight safety.
no code implementations • 24 Feb 2022 • Zhize Wu, Huanyi Li, XiaoFeng Wang, Zijun Wu, Le Zou, Lixiang Xu, Ming Tan
Household garbage images are usually faced with complex backgrounds, variable illuminations, diverse angles, and changeable shapes, which bring a great difficulty in garbage image classification.
no code implementations • 12 Feb 2022 • Zhize Wu, XiaoFeng Wang, Tong Xu, Xuebin Yang, Le Zou, Lixiang Xu, Thomas Weise
We embed a domain classification network in the region proposal network~(RPN) using adversarial learning.
no code implementations • 24 Jun 2021 • Peiyuan Zhu, XiaoFeng Wang, Zisen Sang, Aiquan Yuan, Guodong Cao
Hence, in this paper, we propose a context-aware heterogeneous graph attention network (CHGAT) to dynamically generate the representation of the user and to estimate the probability for future behavior.
1 code implementation • 19 Mar 2021 • Yuxuan Chen, Jiangshan Zhang, Xuejing Yuan, Shengzhi Zhang, Kai Chen, XiaoFeng Wang, Shanqing Guo
In this paper, we present our systematization of knowledge for ASR security and provide a comprehensive taxonomy for existing work based on a modularized workflow.
no code implementations • 18 Feb 2021 • Chengyuan Wu, Dongdong Liu, XiaoFeng Wang, Bo wang
The progenitor systems accounting for explosions of type Ia supernovae (SNe Ia) is still under debate.
Solar and Stellar Astrophysics
no code implementations • 18 Feb 2021 • Jorge Melegati, Eduardo Guerra, XiaoFeng Wang
Regarding the first, it provides a better understanding of the guidance founders use to develop their startups and, for the latter, a technique to identify hypotheses in early-stage software startups.
Computers and Society
no code implementations • 21 Jan 2021 • Xiangyun Zeng, XiaoFeng Wang, Ali Esamdin, Craig Pellegrino, WeiKang Zheng, Jujia Zhang, Jun Mo, Wenxiong Li, D. Andrew Howell, Alexei V. Filippenko, Han Lin, Thomas G. Brink, Edward A. Baron, Jamison Burke, James M. DerKacy, Curtis McCully, Daichi Hiramatsu, Griffin Hosseinzadeh, Benjamin T. Jeffers, Timothy W. Ross, Benjamin E. Stahl, Samantha Stegman, Stefano Valenti, Lifan Wang, Danfeng Xiang, Jicheng Zhang, Tianmeng Zhang
We present extensive, well-sampled optical and ultraviolet photometry and optical spectra of the Type Ia supernova (SN Ia) 2017hpa.
High Energy Astrophysical Phenomena Solar and Stellar Astrophysics
no code implementations • 5 Nov 2020 • Dominic Seyler, Wei Liu, XiaoFeng Wang, ChengXiang Zhai
Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior.
1 code implementation • 20 Oct 2020 • Rabab Abdelfattah, XiaoFeng Wang, Song Wang
Accurate detection and segmentation of transmission towers~(TTs) and power lines~(PLs) from aerial images plays a key role in protecting power-grid security and low-altitude UAV safety.
1 code implementation • 7 Oct 2020 • Paul Ralph, Nauman bin Ali, Sebastian Baltes, Domenico Bianculli, Jessica Diaz, Yvonne Dittrich, Neil Ernst, Michael Felderer, Robert Feldt, Antonio Filieri, Breno Bernard Nicolau de França, Carlo Alberto Furia, Greg Gay, Nicolas Gold, Daniel Graziotin, Pinjia He, Rashina Hoda, Natalia Juristo, Barbara Kitchenham, Valentina Lenarduzzi, Jorge Martínez, Jorge Melegati, Daniel Mendez, Tim Menzies, Jefferson Molleri, Dietmar Pfahl, Romain Robbes, Daniel Russo, Nyyti Saarimäki, Federica Sarro, Janet Siegmund, Diomidis Spinellis, Miroslaw Staron, Klaas Stol, Margaret-Anne Storey, Davide Taibi, Damian Tamburri, Marco Torchiano, Christoph Treude, Burak Turhan, XiaoFeng Wang, Sira Vegas
Empirical Standards are natural-language models of a scientific community's expectations for a specific kind of study (e. g. a questionnaire survey).
Software Engineering General Literature
1 code implementation • RSC advances 2020 • Mingjian Jiang, Zhen Li, Shugang Zhang, Shuang Wang, XiaoFeng Wang, Qing Yuan, Zhiqiang Wei
Computer-aided drug design uses high-performance computers to simulate the tasks in drug design, which is a promising research area.
Ranked #3 on
Drug Discovery
on LIT-PCBA(ALDH1)
no code implementations • 13 Feb 2018 • Di Tang, XiaoFeng Wang, Kehuan Zhang
To launch black-box attacks against a Deep Neural Network (DNN) based Face Recognition (FR) system, one needs to build \textit{substitute} models to simulate the target model, so the adversarial examples discovered from substitute models could also mislead the target model.