3 code implementations • ICLR 2020 • Daniel Keysers, Nathanael Schärli, Nathan Scales, Hylke Buisman, Daniel Furrer, Sergii Kashubin, Nikola Momchev, Danila Sinopalnikov, Lukasz Stafiniak, Tibor Tihon, Dmitry Tsarkov, Xiao Wang, Marc van Zee, Olivier Bousquet
We present a large and realistic natural language question answering dataset that is constructed according to this method, and we use it to analyze the compositional generalization ability of three machine learning architectures.
Ranked #5 on Semantic Parsing on CFQ
3 code implementations • WWW 2019 2019 • Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, P. Yu, Yanfang Ye
With the learned importance from both node-level and semantic-level attention, the importance of node and meta-path can be fully considered.
Ranked #1 on Heterogeneous Node Classification on DBLP (PACT) 14k
Social and Information Networks
4 code implementations • CVPR 2022 • Xiaohua Zhai, Xiao Wang, Basil Mustafa, Andreas Steiner, Daniel Keysers, Alexander Kolesnikov, Lucas Beyer
This paper presents contrastive-tuning, a simple method employing contrastive training to align image and text models while still taking advantage of their pre-training.
1 code implementation • 14 Sep 2023 • Zhiheng Xi, Wenxiang Chen, Xin Guo, wei he, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, Rui Zheng, Xiaoran Fan, Xiao Wang, Limao Xiong, Yuhao Zhou, Weiran Wang, Changhao Jiang, Yicheng Zou, Xiangyang Liu, Zhangyue Yin, Shihan Dou, Rongxiang Weng, Wensen Cheng, Qi Zhang, Wenjuan Qin, Yongyan Zheng, Xipeng Qiu, Xuanjing Huang, Tao Gui
Many efforts have been made to develop intelligent agents, but they mainly focus on advancement in algorithms or training strategies to enhance specific capabilities or performance on particular tasks.
2 code implementations • 12 May 2022 • Matthias Minderer, Alexey Gritsenko, Austin Stone, Maxim Neumann, Dirk Weissenborn, Alexey Dosovitskiy, Aravindh Mahendran, Anurag Arnab, Mostafa Dehghani, Zhuoran Shen, Xiao Wang, Xiaohua Zhai, Thomas Kipf, Neil Houlsby
Combining simple architectures with large-scale pre-training has led to massive improvements in image classification.
Ranked #1 on One-Shot Object Detection on MS COCO
2 code implementations • 7 May 2018 • Ziwei Zhang, Peng Cui, Haoyang Li, Xiao Wang, Wenwu Zhu
Network embedding, which learns low-dimensional vector representation for nodes in the network, has attracted considerable research attention recently.
2 code implementations • AAAI 2017 • Xiao Wang, Peng Cui, Jing Wang, Jian Pei, Wenwu Zhu, Shiqiang Yang
While previous network embedding methods primarily preserve the microscopic structure, such as the first- and second-order proximities of nodes, the mesoscopic community structure, which is one of the most prominent feature of networks, is largely ignored.
1 code implementation • 14 Sep 2022 • Xi Chen, Xiao Wang, Soravit Changpinyo, AJ Piergiovanni, Piotr Padlewski, Daniel Salz, Sebastian Goodman, Adam Grycner, Basil Mustafa, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Nan Ding, Keran Rong, Hassan Akbari, Gaurav Mishra, Linting Xue, Ashish Thapliyal, James Bradbury, Weicheng Kuo, Mojtaba Seyedhosseini, Chao Jia, Burcu Karagol Ayan, Carlos Riquelme, Andreas Steiner, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
PaLI generates text based on visual and textual inputs, and with this interface performs many vision, language, and multimodal tasks, in many languages.
1 code implementation • 30 Mar 2023 • Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic, Andreas Steiner, Alexander Kolesnikov, André Susano Pinto, Emanuele Bugliarello, Xiao Wang, Qihang Yu, Liang-Chieh Chen, Xiaohua Zhai
A key finding is that a small decoder learned on top of a frozen pretrained encoder works surprisingly well.
1 code implementation • NeurIPS 2023 • Jannik Kossen, Mark Collier, Basil Mustafa, Xiao Wang, Xiaohua Zhai, Lucas Beyer, Andreas Steiner, Jesse Berent, Rodolphe Jenatton, Efi Kokiopoulou
With 3T, we propose a more flexible strategy that allows the image tower to benefit from both pretrained embeddings and contrastive training.
1 code implementation • 11 Jan 2024 • Binghai Wang, Rui Zheng, Lu Chen, Yan Liu, Shihan Dou, Caishuang Huang, Wei Shen, Senjie Jin, Enyu Zhou, Chenyu Shi, Songyang Gao, Nuo Xu, Yuhao Zhou, Xiaoran Fan, Zhiheng Xi, Jun Zhao, Xiao Wang, Tao Ji, Hang Yan, Lixing Shen, Zhan Chen, Tao Gui, Qi Zhang, Xipeng Qiu, Xuanjing Huang, Zuxuan Wu, Yu-Gang Jiang
We introduce a series of novel methods to mitigate the influence of incorrect and ambiguous preferences in the dataset and fully leverage high-quality preference data.
2 code implementations • 17 Nov 2022 • Xiao Wang, Zongzhen Wu, Bo Jiang, Zhimin Bao, Lin Zhu, Guoqi Li, YaoWei Wang, Yonghong Tian
The main streams of human activity recognition (HAR) algorithms are developed based on RGB cameras which are suffered from illumination, fast motion, privacy-preserving, and large energy consumption.
3 code implementations • 19 May 2021 • Xiao Wang, Nian Liu, Hui Han, Chuan Shi
Then the cross-view contrastive learning, as well as a view mask mechanism, is proposed, which is able to extract the positive and negative embeddings from two views.
1 code implementation • 22 Jan 2019 • Xiao Wang, Shaofei Zheng, Rui Yang, Aihua Zheng, Zhe Chen, Jin Tang, Bin Luo
We also review some popular network architectures which have been widely applied in the deep learning community.
2 code implementations • 4 Dec 2023 • Jiandong Jin, Xiao Wang, Chenglong Li, Lili Huang, Jin Tang
Then, a Transformer decoder is proposed to generate the human attributes by incorporating the visual features and attribute query tokens.
2 code implementations • 17 Dec 2023 • Xiao Wang, Jiandong Jin, Chenglong Li, Jin Tang, Cheng Zhang, Wei Wang
In this paper, we formulate PAR as a vision-language fusion problem and fully exploit the relations between pedestrian images and attribute labels.
1 code implementation • ACL 2021 • Tao Gui, Xiao Wang, Qi Zhang, Qin Liu, Yicheng Zou, Xin Zhou, Rui Zheng, Chong Zhang, Qinzhuo Wu, Jiacheng Ye, Zexiong Pang, Yongxin Zhang, Zhengyan Li, Ruotian Ma, Zichu Fei, Ruijian Cai, Jun Zhao, Xingwu Hu, Zhiheng Yan, Yiding Tan, Yuan Hu, Qiyuan Bian, Zhihua Liu, Bolin Zhu, Shan Qin, Xiaoyu Xing, Jinlan Fu, Yue Zhang, Minlong Peng, Xiaoqing Zheng, Yaqian Zhou, Zhongyu Wei, Xipeng Qiu, Xuanjing Huang
To guarantee user acceptability, all the text transformations are linguistically based, and we provide a human evaluation for each one.
1 code implementation • ICCV 2021 • Zhipeng Zhang, Yihao Liu, Xiao Wang, Bing Li, Weiming Hu
Siamese tracking has achieved groundbreaking performance in recent years, where the essence is the efficient matching operator cross-correlation and its variants.
2 code implementations • CVPR 2021 • Xiao Wang, Xiujun Shu, Zhipeng Zhang, Bo Jiang, YaoWei Wang, Yonghong Tian, Feng Wu
We believe this benchmark will greatly boost related researches on natural language guided tracking.
Ranked #3 on Visual Object Tracking on TNL2K (precision metric)
4 code implementations • 26 Sep 2023 • Xiao Wang, Shiao Wang, Chuanming Tang, Lin Zhu, Bo Jiang, Yonghong Tian, Jin Tang
Tracking using bio-inspired event cameras has drawn more and more attention in recent years.
1 code implementation • 27 Nov 2017 • Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu
By setting a maximum tolerated error as a threshold, we can trigger SVD restart automatically when the margin exceeds this threshold. We prove that the time complexity of our method is linear with respect to the number of local dynamic changes, and our method is general across different types of dynamic networks.
Social and Information Networks
1 code implementation • 17 Apr 2023 • Xiao Wang, Weikang Zhou, Can Zu, Han Xia, Tianze Chen, Yuansen Zhang, Rui Zheng, Junjie Ye, Qi Zhang, Tao Gui, Jihua Kang, Jingsheng Yang, Siyuan Li, Chunsai Du
Large language models have unlocked strong multi-task capabilities from reading instructive prompts.
Ranked #2 on Zero-shot Named Entity Recognition (NER) on CrossNER (using extra training data)
1 code implementation • 15 Apr 2024 • Xiao Wang, Shiao Wang, Yuhe Ding, Yuehang Li, Wentao Wu, Yao Rong, Weizhe Kong, Ju Huang, Shihao Li, Haoxiang Yang, Ziwen Wang, Bo Jiang, Chenglong Li, YaoWei Wang, Yonghong Tian, Jin Tang
In this paper, we give the first comprehensive review of these works and also provide experimental comparisons and analysis to better demonstrate the features and advantages of SSM.
1 code implementation • 10 Jan 2024 • Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Yuan Li, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bertie Vidgen, Bhavya Kailkhura, Caiming Xiong, Chaowei Xiao, Chunyuan Li, Eric Xing, Furong Huang, Hao liu, Heng Ji, Hongyi Wang, huan zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, Joaquin Vanschoren, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S. Yu, Pin-Yu Chen, Quanquan Gu, ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, William Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yong Chen, Yue Zhao
This paper introduces TrustLLM, a comprehensive study of trustworthiness in LLMs, including principles for different dimensions of trustworthiness, established benchmark, evaluation, and analysis of trustworthiness for mainstream LLMs, and discussion of open challenges and future directions.
1 code implementation • 20 Feb 2023 • Xiao Wang, Guangyao Chen, Guangwu Qian, Pengcheng Gao, Xiao-Yong Wei, YaoWei Wang, Yonghong Tian, Wen Gao
We also give visualization and analysis of the model parameters and results on representative downstream tasks.
2 code implementations • 5 Feb 2020 • Deyu Bo, Xiao Wang, Chuan Shi, Meiqi Zhu, Emiao Lu, Peng Cui
The strength of deep clustering methods is to extract the useful representations from the data itself, rather than the structure of data, which receives scarce attention in representation learning.
1 code implementation • 18 Mar 2024 • Weikang Zhou, Xiao Wang, Limao Xiong, Han Xia, Yingshuang Gu, Mingxu Chai, Fukang Zhu, Caishuang Huang, Shihan Dou, Zhiheng Xi, Rui Zheng, Songyang Gao, Yicheng Zou, Hang Yan, Yifan Le, Ruohui Wang, Lijun Li, Jing Shao, Tao Gui, Qi Zhang, Xuanjing Huang
This paper introduces EasyJailbreak, a unified framework simplifying the construction and evaluation of jailbreak attacks against LLMs.
1 code implementation • 10 Feb 2023 • Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin F. Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Patrick Collier, Alexey Gritsenko, Vighnesh Birodkar, Cristina Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetić, Dustin Tran, Thomas Kipf, Mario Lučić, Xiaohua Zhai, Daniel Keysers, Jeremiah Harmsen, Neil Houlsby
The scaling of Transformers has driven breakthrough capabilities for language models.
Ranked #1 on Zero-Shot Transfer Image Classification on ObjectNet
2 code implementations • CVPR 2021 • Qianjiang Hu, Xiao Wang, Wei Hu, Guo-Jun Qi
Contrastive learning relies on constructing a collection of negative examples that are sufficiently hard to discriminate against positive queries when their representations are self-trained.
2 code implementations • 14 Jan 2022 • Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi
Furthermore, we maintain the performance of estimated views and the final view and reduce the mutual information of every two views.
1 code implementation • 11 Feb 2022 • Yabin Zhu, Chenglong Li, Yao Liu, Xiao Wang, Jin Tang, Bin Luo, Zhixiang Huang
Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection and segmentation.
1 code implementation • 13 Oct 2023 • Xi Chen, Xiao Wang, Lucas Beyer, Alexander Kolesnikov, Jialin Wu, Paul Voigtlaender, Basil Mustafa, Sebastian Goodman, Ibrahim Alabdulmohsin, Piotr Padlewski, Daniel Salz, Xi Xiong, Daniel Vlasic, Filip Pavetic, Keran Rong, Tianli Yu, Daniel Keysers, Xiaohua Zhai, Radu Soricut
This paper presents PaLI-3, a smaller, faster, and stronger vision language model (VLM) that compares favorably to similar models that are 10x larger.
Ranked #2 on Temporal/Casual QA on NExT-QA (using extra training data)
1 code implementation • 22 Oct 2023 • Xiao Wang, Tianze Chen, Qiming Ge, Han Xia, Rong Bao, Rui Zheng, Qi Zhang, Tao Gui, Xuanjing Huang
In this paper, we propose orthogonal low-rank adaptation (O-LoRA), a simple and efficient approach for continual learning in language models, effectively mitigating catastrophic forgetting while learning new tasks.
2 code implementations • 11 Aug 2021 • Xiao Wang, Jianing Li, Lin Zhu, Zhipeng Zhang, Zhe Chen, Xin Li, YaoWei Wang, Yonghong Tian, Feng Wu
Different from visible cameras which record intensity images frame by frame, the biologically inspired event camera produces a stream of asynchronous and sparse events with much lower latency.
Ranked #1 on Object Tracking on VisEvent
2 code implementations • 20 Nov 2022 • Chuanming Tang, Xiao Wang, Ju Huang, Bo Jiang, Lin Zhu, Jianlin Zhang, YaoWei Wang, Yonghong Tian
In this paper, we propose a single-stage backbone network for Color-Event Unified Tracking (CEUTrack), which achieves the above functions simultaneously.
Ranked #3 on Object Tracking on COESOT
1 code implementation • CVPR 2022 • Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen
Many recent self-supervised frameworks for visual representation learning are based on certain forms of Siamese networks.
1 code implementation • 4 Jan 2021 • Deyu Bo, Xiao Wang, Chuan Shi, HuaWei Shen
For a deeper understanding, we theoretically analyze the roles of low-frequency signals and high-frequency signals on learning node representations, which further explains why FAGCN can perform well on different types of networks.
1 code implementation • CVPR 2022 • Jiahua Dong, Lixu Wang, Zhen Fang, Gan Sun, Shichao Xu, Xiao Wang, Qi Zhu
It makes the global model suffer from significant catastrophic forgetting on old classes in real-world scenarios, where local clients often collect new classes continuously and have very limited storage memory to store old classes.
1 code implementation • 15 Dec 2023 • Shihan Dou, Enyu Zhou, Yan Liu, Songyang Gao, Jun Zhao, Wei Shen, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Xiaoran Fan, ShiLiang Pu, Jiang Zhu, Rui Zheng, Tao Gui, Qi Zhang, Xuanjing Huang
Supervised fine-tuning (SFT) is a crucial step for large language models (LLMs), enabling them to align with human instructions and enhance their capabilities in downstream tasks.
2 code implementations • 21 Nov 2019 • Xiao Wang, Daisuke Kihara, Jiebo Luo, Guo-Jun Qi
In this study, we propose a new EnAET framework to further improve existing semi-supervised methods with self-supervised information.
Ranked #1 on Semi-Supervised Image Classification on STL-10
2 code implementations • 14 Aug 2020 • Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu
Our experiments demonstrate the importance of acknowledging class imbalance and taking measures as early as possible in FL training, and the effectiveness of our method in mitigating the impact.
3 code implementations • 21 Jun 2021 • Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis
In particular, based on the pseudo-relevant set of documents identified using a first-pass dense retrieval, we extract representative feedback embeddings (using KMeans clustering) -- while ensuring that these embeddings discriminate among passages (based on IDF) -- which are then added to the query representation.
Ranked #1 on TREC 2019 Passage Ranking on MSMARCO
1 code implementation • 26 Jul 2022 • Chaofei Hong, Mengwen Yuan, Mengxiao Zhang, Xiao Wang, Chegnjun Zhang, Jiaxin Wang, Gang Pan, Zhaohui Wu, Huajin Tang
In this work, we present a Python based spiking neural network (SNN) simulation and training framework, aka SPAIC that aims to support brain-inspired model and algorithm researches integrated with features from both deep learning and neuroscience.
2 code implementations • 29 May 2023 • Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, AJ Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture.
Ranked #1 on Fine-Grained Image Recognition on OVEN
1 code implementation • 3 Feb 2024 • Lixu Wang, Yang Zhao, Jiahua Dong, Ating Yin, Qinbin Li, Xiao Wang, Dusit Niyato, Qi Zhu
Federated Learning (FL) is a privacy-preserving distributed learning approach that is rapidly developing in an era where privacy protection is increasingly valued.
1 code implementation • 25 Nov 2019 • Xiao Wang, Ruijia Wang, Chuan Shi, Guojie Song, Qingyong Li
The interactions of users and items in recommender system could be naturally modeled as a user-item bipartite graph.
1 code implementation • 15 Apr 2021 • Xiao Wang, Guo-Jun Qi
Thus, we propose a general framework called Contrastive Learning with Stronger Augmentations~(CLSA) to complement current contrastive learning approaches.
1 code implementation • CVPR 2022 • Lin Zhu, Xiao Wang, Yi Chang, Jianing Li, Tiejun Huang, Yonghong Tian
We propose a novel Event-based Video reconstruction framework based on a fully Spiking Neural Network (EVSNN), which utilizes Leaky-Integrate-and-Fire (LIF) neuron and Membrane Potential (MP) neuron.
Computational Efficiency Event-Based Video Reconstruction +2
1 code implementation • 28 Nov 2017 • Ke Tu, Peng Cui, Xiao Wang, Fei Wang, Wenwu Zhu
These hyper-networks pose great challenges to existing network embedding methods when the hyperedges are indecomposable, that is to say, any subset of nodes in a hyperedge cannot form another hyperedge.
Social and Information Networks
1 code implementation • 5 Jul 2021 • Xin Cai, BoYu Chen, Jiabei Zeng, Jiajun Zhang, Yunjia Sun, Xiao Wang, Zhilong Ji, Xiao Liu, Xilin Chen, Shiguang Shan
This paper presents a method for gaze estimation according to face images.
2 code implementations • 31 May 2021 • Xiujun Shu, Xiao Wang, Xianghao Zang, Shiliang Zhang, Yuanqi Chen, Ge Li, Qi Tian
We also verified that models pre-trained on LaST can generalize well on existing datasets with short-term and cloth-changing scenarios.
2 code implementations • 25 Jan 2023 • Chenxi Liu, Lixu Wang, Lingjuan Lyu, Chen Sun, Xiao Wang, Qi Zhu
To overcome these limitations of DA and DG in handling the Unfamiliar Period during continual domain shift, we propose RaTP, a framework that focuses on improving models' target domain generalization (TDG) capability, while also achieving effective target domain adaptation (TDA) capability right after training on certain domains and forgetting alleviation (FA) capability on past domains.
1 code implementation • 10 Oct 2023 • Xiao Wang, Yuansen Zhang, Tianze Chen, Songyang Gao, Senjie Jin, Xianjun Yang, Zhiheng Xi, Rui Zheng, Yicheng Zou, Tao Gui, Qi Zhang, Xuanjing Huang
In this paper, we introduce TRACE, a novel benchmark designed to evaluate continual learning in LLMs.
3 code implementations • 9 Mar 2024 • Xiao Wang, Ju Huang, Shiao Wang, Chuanming Tang, Bo Jiang, Yonghong Tian, Jin Tang, Bin Luo
Current event-/frame-event based trackers undergo evaluation on short-term tracking datasets, however, the tracking of real-world scenarios involves long-term tracking, and the performance of existing tracking algorithms in these scenarios remains unclear.
1 code implementation • 2 Feb 2024 • Shihan Dou, Yan Liu, Haoxiang Jia, Limao Xiong, Enyu Zhou, Wei Shen, Junjie Shan, Caishuang Huang, Xiao Wang, Xiaoran Fan, Zhiheng Xi, Yuhao Zhou, Tao Ji, Rui Zheng, Qi Zhang, Xuanjing Huang, Tao Gui
The advancement of large language models (LLMs) has significantly propelled the field of code generation.
1 code implementation • 10 Sep 2019 • Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S. Yu, Yanfang Ye
The micro-dynamics describe the formation process of network structures in a detailed manner, while the macro-dynamics refer to the evolution pattern of the network scale.
1 code implementation • 28 Sep 2022 • Shaohua Fan, Xiao Wang, Yanhu Mo, Chuan Shi, Jian Tang
However, by presenting a graph classification investigation on the training graphs with severe bias, surprisingly, we discover that GNNs always tend to explore the spurious correlations to make decision, even if the causal correlation always exists.
1 code implementation • 17 Oct 2023 • Bo Jiang, Zitian Wang, Xixi Wang, Ziyan Zhang, Lan Chen, Xiao Wang, Bin Luo
Then, each pixel of feature map is regarded as a graph node and the graph neural network is proposed to model the structured information for coarse change map prediction.
2 code implementations • ACL 2022 • Xiao Wang, Shihan Dou, Limao Xiong, Yicheng Zou, Qi Zhang, Tao Gui, Liang Qiao, Zhanzhan Cheng, Xuanjing Huang
NER model has achieved promising performance on standard NER benchmarks.
Ranked #8 on Named Entity Recognition (NER) on WNUT 2017
1 code implementation • CVPR 2023 • Ziyue Zhu, Qiang Meng, Xiao Wang, Ke Wang, Liujiang Yan, Jian Yang
For the loss design, we propose the COMLoss to dynamically predict object-level difficulties and emphasize objects of different difficulties based on training stages.
1 code implementation • 5 Oct 2022 • Nian Liu, Xiao Wang, Deyu Bo, Chuan Shi, Jian Pei
Then we theoretically prove that GCL is able to learn the invariance information by contrastive invariance theorem, together with our GAME rule, for the first time, we uncover that the learned representations by GCL essentially encode the low-frequency information, which explains why GCL works.
1 code implementation • ICLR 2022 • Lixu Wang, Shichao Xu, Ruiqi Xu, Xiao Wang, Qi Zhu
Our NTL-based authorization approach instead provides data-centric protection, which we call applicability authorization, by significantly degrading the performance of the model on unauthorized data.
1 code implementation • ICLR 2021 • Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
There is currently no method that enables machine learning in such a setting, where both confidentiality and privacy need to be preserved, to prevent both explicit and implicit sharing of data.
1 code implementation • 18 Feb 2022 • Tianyu Zhao, Cheng Yang, Yibo Li, Quan Gan, Zhenyi Wang, Fengqi Liang, Huan Zhao, Yingxia Shao, Xiao Wang, Chuan Shi
Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due to diverse architectures and applied scenarios.
1 code implementation • 6 Oct 2022 • Ruijia Wang, Xiao Wang, Chuan Shi, Le Song
Recent studies show that graph convolutional network (GCN) often performs worse for low-degree nodes, exhibiting the so-called structural unfairness for graphs with long-tailed degree distributions prevalent in the real world.
1 code implementation • 8 Feb 2024 • Zhiheng Xi, Wenxiang Chen, Boyang Hong, Senjie Jin, Rui Zheng, wei he, Yiwen Ding, Shichun Liu, Xin Guo, Junzhe Wang, Honglin Guo, Wei Shen, Xiaoran Fan, Yuhao Zhou, Shihan Dou, Xiao Wang, Xinbo Zhang, Peng Sun, Tao Gui, Qi Zhang, Xuanjing Huang
In this paper, we propose R$^3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language models.
1 code implementation • 24 Jul 2021 • Xiujun Shu, Ge Li, Xiao Wang, Weijian Ruan, Qi Tian
The key to this task is to exploit cloth-irrelevant cues.
1 code implementation • 20 Apr 2023 • Jun Zhu, Jiandong Jin, Zihan Yang, Xiaohao Wu, Xiao Wang
The averaged visual tokens and text tokens are concatenated and fed into a fusion Transformer for multi-modal interactive learning.
1 code implementation • NeurIPS 2021 • Di Jin, Zhizhi Yu, Cuiying Huo, Rui Wang, Xiao Wang, Dongxiao He, Jiawei Han
So can we reasonably utilize these segmentation rules to design a universal propagation mechanism independent of the network structural assumption?
1 code implementation • 27 Mar 2022 • Xiao Wang, Yuhang Huang, Dan Zeng, Guo-Jun Qi
It trains an encoder by distinguishing positive samples from negative ones given query anchors.
Ranked #65 on Self-Supervised Image Classification on ImageNet
1 code implementation • 30 Nov 2023 • Dong Li, Jiandong Jin, Yuhao Zhang, Yanlin Zhong, Yaoyang Wu, Lan Chen, Xiao Wang, Bin Luo
Current methods typically employ backbone networks to individually extract the features of RGB frames and event streams, and subsequently fuse these features for pattern recognition.
1 code implementation • 15 Dec 2023 • Xiao Wang, Wentao Wu, Chenglong Li, Zhicheng Zhao, Zhe Chen, Yukai Shi, Jin Tang
To address this issue, we propose a novel vehicle-centric pre-training framework called VehicleMAE, which incorporates the structural information including the spatial structure from vehicle profile information and the semantic structure from informative high-level natural language descriptions for effective masked vehicle appearance reconstruction.
2 code implementations • NeurIPS 2021 • Xiao Wang, Hongrui Liu, Chuan Shi, Cheng Yang
Specifically, we first verify that the confidence distribution in a graph has homophily property, and this finding inspires us to design a calibration GNN model (CaGCN) to learn the calibration function.
1 code implementation • 18 Aug 2022 • Xiujun Shu, Wei Wen, Haoqian Wu, Keyu Chen, Yiran Song, Ruizhi Qiao, Bo Ren, Xiao Wang
To explore the fine-grained alignment, we further propose two implicit semantic alignment paradigms: multi-level alignment (MLA) and bidirectional mask modeling (BMM).
2 code implementations • 22 Jul 2021 • Xiao Wang, Xiujun Shu, Shiliang Zhang, Bo Jiang, YaoWei Wang, Yonghong Tian, Feng Wu
The visible and thermal filters will be used to conduct a dynamic convolutional operation on their corresponding input feature maps respectively.
Ranked #21 on Rgb-T Tracking on RGBT234
1 code implementation • 20 Nov 2021 • Shaohua Fan, Xiao Wang, Chuan Shi, Peng Cui, Bai Wang
Graph Neural Networks (GNNs) are proposed without considering the agnostic distribution shifts between training and testing graphs, inducing the degeneration of the generalization ability of GNNs on Out-Of-Distribution (OOD) settings.
1 code implementation • 19 May 2022 • Xiao Wang, Zhe Chen, Bo Jiang, Jin Tang, Bin Luo, DaCheng Tao
To track the target in a video, current visual trackers usually adopt greedy search for target object localization in each frame, that is, the candidate region with the maximum response score will be selected as the tracking result of each frame.
1 code implementation • 18 Aug 2022 • Chuanming Tang, Xiao Wang, Yuanchao Bai, Zhe Wu, Jianlin Zhang, YongMei Huang
To handle these issues, in this paper, we propose a unified Spatial-Frequency Transformer that models the Gaussian spatial Prior and High-frequency emphasis Attention (GPHA) simultaneously.
1 code implementation • 13 Jun 2023 • Yizhen Zheng, He Zhang, Vincent CS Lee, Yu Zheng, Xiao Wang, Shirui Pan
Real-world graphs generally have only one kind of tendency in their connections.
1 code implementation • 8 Aug 2023 • Xiao Wang, Zongzhen Wu, Yao Rong, Lin Zhu, Bo Jiang, Jin Tang, Yonghong Tian
Secondly, they adopt either Spiking Neural Networks (SNN) for energy-efficient recognition with suboptimal results, or Artificial Neural Networks (ANN) for energy-intensive, high-performance recognition.
1 code implementation • 21 Dec 2023 • Yingzhou Lu, Minjie Shen, Yue Zhao, Chenhao Li, Fan Meng, Xiao Wang, David Herrington, Yue Wang, Tim Fu, Capucine van Rechem
With GenoCraft, researchers and data scientists have access to an array of cutting-edge bioinformatics tools under a user-friendly interface, making it a valuable resource for managing and analyzing large-scale omics data.
3 code implementations • 13 Jun 2022 • Luca Gagliardi, Andrea Raffo, Ulderico Fugacci, Silvia Biasotti, Walter Rocchia, Hao Huang, Boulbaba Ben Amor, Yi Fang, Yuanyuan Zhang, Xiao Wang, Charles Christoffer, Daisuke Kihara, Apostolos Axenopoulos, Stelios Mylonas, Petros Daras
This paper presents the methods that have participated in the SHREC 2022 contest on protein-ligand binding site recognition.
1 code implementation • 21 Dec 2019 • Bo Jiang, Zitai Zhou, Xiao Wang, Jin Tang, Bin Luo
Fusing complementary information of RGB and depth has been demonstrated to be effective for image salient object detection which is known as RGB-D salient object detection problem.
1 code implementation • 9 Jun 2021 • Xiao Wang, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu
In this paper, we propose a novel and general target-aware attention mechanism (termed TANet) and integrate it with tracking-by-detection framework to conduct joint local and global search for robust tracking.
1 code implementation • 5 Jan 2024 • Yabin Zhu, Xiao Wang, Chenglong Li, Bo Jiang, Lin Zhu, Zhixiang Huang, Yonghong Tian, Jin Tang
In this work, we formally propose the task of object tracking using unaligned neuromorphic and visible cameras.
1 code implementation • 21 Jan 2024 • Songyang Gao, Qiming Ge, Wei Shen, Shihan Dou, Junjie Ye, Xiao Wang, Rui Zheng, Yicheng Zou, Zhi Chen, Hang Yan, Qi Zhang, Dahua Lin
This reliance limits the applicability of RLHF and hinders the development of professional assistants tailored to diverse human preferences.
1 code implementation • 23 Jan 2024 • Yanhu Mo, Xiao Wang, Shaohua Fan, Chuan Shi
How can we fix it and encourage the current GCL to learn better invariant representations?
1 code implementation • 6 Dec 2019 • Yiding Zhang, Xiao Wang, Xunqiang Jiang, Chuan Shi, Yanfang Ye
Graph neural network (GNN) has shown superior performance in dealing with graphs, which has attracted considerable research attention recently.
1 code implementation • 30 Mar 2021 • Xiao Wang, Zhe Chen, Jin Tang, Bin Luo, YaoWei Wang, Yonghong Tian, Feng Wu
In this paper, we propose to introduce more dynamics by devising a dynamic attention-guided multi-trajectory tracking strategy.
2 code implementations • 1 Dec 2023 • Xiao Wang, Yaoyu Li, Tian Gan, Zheng Zhang, Jingjing Lv, Liqiang Nie
Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting in promising outcomes due to the shared knowledge between images and videos.
Ranked #9 on Video Retrieval on MSR-VTT-1kA
1 code implementation • 8 Apr 2023 • Yixuan Qiu, Xiao Wang
Sampling from high-dimensional distributions is a fundamental problem in statistical research and practice.
1 code implementation • 14 Dec 2017 • Karl Zhanghao, Xingye Chen, Wenhui Liu, Meiqi Li, Chunyan Shan, Xiao Wang, Kun Zhao, Amit Lai, Hao Xie, Qionghai Dai, Peng Xi
The dipole nature of chromophore is important for both super-resolution microscopy and imaging molecular structure, which is nevertheless neglected in most microscopies, even including structured illumination microscopy (SIM) with polarized excitations.
Optics
1 code implementation • ICLR 2020 • Yixuan Qiu, Lingsong Zhang, Xiao Wang
The contrastive divergence algorithm is a popular approach to training energy-based latent variable models, which has been widely used in many machine learning models such as the restricted Boltzmann machines and deep belief nets.
1 code implementation • 26 Feb 2024 • Huijie Lv, Xiao Wang, Yuansen Zhang, Caishuang Huang, Shihan Dou, Junjie Ye, Tao Gui, Qi Zhang, Xuanjing Huang
Adversarial misuse, particularly through `jailbreaking' that circumvents a model's safety and ethical protocols, poses a significant challenge for Large Language Models (LLMs).
1 code implementation • NeurIPS 2023 • Donglin Xia, Xiao Wang, Nian Liu, Chuan Shi
To address this challenge, we propose the Cluster Information Transfer (CIT) mechanism (Code available at https://github. com/BUPT-GAMMA/CITGNN), which can learn invariant representations for GNNs, thereby improving their generalization ability to various and unknown test graphs with structure shift.
1 code implementation • 20 Aug 2019 • Xiao Wang, Siyue Wang, Pin-Yu Chen, Yanzhi Wang, Brian Kulis, Xue Lin, Peter Chin
However, one critical drawback of current defenses is that the robustness enhancement is at the cost of noticeable performance degradation on legitimate data, e. g., large drop in test accuracy.
1 code implementation • 30 Nov 2022 • Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi
In a dynamic graph, we propose to simultaneously estimate contemporaneous relationships and time-lagged interaction relationships between the node features.
1 code implementation • 15 Mar 2023 • Xiao Wang, Tian Gan, Yinwei Wei, Jianlong Wu, Dai Meng, Liqiang Nie
Existing methods mostly focus on analyzing video content, neglecting users' social influence and tag relation.
1 code implementation • 22 May 2023 • Xiao Wang, Weikang Zhou, Qi Zhang, Jie zhou, Songyang Gao, Junzhe Wang, Menghan Zhang, Xiang Gao, Yunwen Chen, Tao Gui
Pretrained language models have achieved remarkable success in various natural language processing tasks.
1 code implementation • 8 Jun 2023 • Bo Jiang, Chengguo Yuan, Xiao Wang, Zhimin Bao, Lin Zhu, Yonghong Tian, Jin Tang
To address these issues, we propose a novel dual point-voxel absorbing graph representation learning for event stream data representation.
1 code implementation • 14 Aug 2023 • Tian Gan, Xiao Wang, Yan Sun, Jianlong Wu, Qingpei Guo, Liqiang Nie
The goal of TSGSV is to evaluate the relevance between a video stream and a given sentence query.
1 code implementation • 23 Aug 2023 • Chengguo Yuan, Yu Jin, Zongzhen Wu, Fanting Wei, Yangzirui Wang, Lan Chen, Xiao Wang
Additionally, a bottleneck Transformer is introduced to facilitate the fusion of the dual-stream information.
1 code implementation • 27 Jan 2022 • Hongrui Liu, Binbin Hu, Xiao Wang, Chuan Shi, Zhiqiang Zhang, Jun Zhou
To this end, in this paper, we propose a novel Distribution Recovered Graph Self-Training framework (DR-GST), which could recover the distribution of the original labeled dataset.
2 code implementations • 26 Jul 2022 • Yukai Shi, Hao Li, Sen Zhang, Zhijing Yang, Xiao Wang
Inspired by the observation that the contrastive relationship could also exist between the criteria, in this work, we propose a novel training paradigm for RealSR, named Criteria Comparative Learning (Cria-CL), by developing contrastive losses defined on criteria instead of image patches.
1 code implementation • 27 Jun 2023 • Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan
Adversarial training is one of the best-performing methods in improving the robustness of deep language models.
1 code implementation • 18 Dec 2023 • Xiao Wang, Yao Rong, Shiao Wang, Yuan Chen, Zhe Wu, Bo Jiang, Yonghong Tian, Jin Tang
It is intuitive to combine them for high-performance RGB-Event based video recognition, however, existing works fail to achieve a good balance between the accuracy and model parameters, as shown in Fig.~\ref{firstimage}.
1 code implementation • NeurIPS 2023 • Yue Yu, Xiao Wang, Mengmei Zhang, Nian Liu, Chuan Shi
To this end, we propose the PrOvable Training (POT) for GCL, which regularizes the training of GCL to encode node embeddings that follows the GCL principle better.
1 code implementation • 10 Mar 2024 • Lin Zhu, Xianzhang Chen, Xiao Wang, Hua Huang
Our framework exhibits a substantial margin of improvement in capturing and highlighting visual saliency in the spike stream, which not only provides a new perspective for spike-based saliency segmentation but also shows a new paradigm for full SNN-based transformer models.
1 code implementation • 30 Sep 2021 • Xiao Wang, Jingen Liu, Tao Mei, Jiebo Luo
Unlike the mainstream clustering-based methods, our framework exploits a transformer-based feature reconstruction scheme to detect event boundary by reconstruction errors.
1 code implementation • 14 Mar 2023 • Xiao Wang, Ying Wang, Ziwei Xuan, Guo-Jun Qi
A criterion in unsupervised pretraining is the pretext task needs to be sufficiently hard to prevent the transformer encoder from learning trivial low-level features not generalizable well to downstream tasks.
1 code implementation • 21 May 2023 • Limao Xiong, Jie zhou, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan
Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.
1 code implementation • 20 Jan 2024 • Haoxiang Yang, Chengguo Yuan, Yabin Zhu, Lan Chen, Xiao Wang, Jin Tang
The mainstream human activity recognition (HAR) algorithms are developed based on RGB cameras, which are easily influenced by low-quality images (e. g., low illumination, motion blur).
1 code implementation • 7 Jul 2020 • Bo Jiang, Sheng Wang, Xiao Wang, Aihua Zheng
Specifically, STADB first obtains an attention map by channel-wise pooling and returns a drop mask by thresholding the attention map.
1 code implementation • 28 Jan 2021 • Meiqi Zhu, Xiao Wang, Chuan Shi, Houye Ji, Peng Cui
Graph Neural Networks (GNNs) have received considerable attention on graph-structured data learning for a wide variety of tasks.
1 code implementation • 10 Aug 2023 • Haoju Leng, Ruining Deng, Shunxing Bao, Dazheng Fang, Bryan A. Millis, Yucheng Tang, Haichun Yang, Xiao Wang, Yifan Peng, Lipeng Wan, Yuankai Huo
The performance evaluation encompasses two key scenarios: (1) a pure CPU-based image analysis scenario ("CPU scenario"), and (2) a GPU-based deep learning framework scenario ("GPU scenario").
1 code implementation • 7 Feb 2024 • Hailiang Li, Yan Huo, Yan Wang, Xu Yang, Miaohui Hao, Xiao Wang
As the modern CPU, GPU, and NPU chip design complexity and transistor counts keep increasing, and with the relentless shrinking of semiconductor technology nodes to nearly 1 nanometer, the placement and routing have gradually become the two most pivotal processes in modern very-large-scale-integrated (VLSI) circuit back-end design.
no code implementations • 5 Feb 2018 • Xi Chen, Xiao Wang, Jianhua Xuan
Considering the ambiguity caused by the occlusion among multiple moving objects, we apply an unscented Kalman filtering (UKF) technique for reliable object detection and tracking.
no code implementations • 22 Jan 2018 • Ming Zeng, Tong Yu, Xiao Wang, Le T. Nguyen, Ole J. Mengshoel, Ian Lane
Labeled data used for training activity recognition classifiers are usually limited in terms of size and diversity.
no code implementations • 6 Apr 2017 • Yixi Xu, Jean Honorio, Xiao Wang
In this paper, we propose a compositional nonparametric method in which a model is expressed as a labeled binary tree of $2k+1$ nodes, where each node is either a summation, a multiplication, or the application of one of the $q$ basis functions to one of the $p$ covariates.
no code implementations • 28 Jul 2017 • Ziliang Chen, Keze Wang, Xiao Wang, Pai Peng, Ebroul Izquierdo, Liang Lin
Aiming at improving performance of visual classification in a cost-effective manner, this paper proposes an incremental semi-supervised learning paradigm called Deep Co-Space (DCS).
no code implementations • 5 Jul 2016 • Xiao Wang, Shiqian Ma, Donald Goldfarb, Wei Liu
In this paper we study stochastic quasi-Newton methods for nonconvex stochastic optimization, where we assume that noisy information about the gradients of the objective function is available via a stochastic first-order oracle (SFO).
no code implementations • 1 May 2017 • Ziyi Liu, Siyu Yu, Xiao Wang, Nanning Zheng
Experiments show that our unsupervised approach is efficient and robust for detecting drivable area for self-driving cars.
no code implementations • 27 May 2016 • Yao Chen, Xiao Wang, Linglong Kong, Hongtu Zhu
Identification of regions of interest (ROI) associated with certain disease has a great impact on public health.
no code implementations • 25 May 2016 • Simeng Qu, Xiao Wang
Dictionary learning is a cutting-edge area in imaging processing, that has recently led to state-of-the-art results in many signal processing tasks.
no code implementations • 13 Sep 2018 • Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David Kaeli, Peter Chin, Xue Lin
Based on the observations of the effect of test dropout rate on test accuracy and attack success rate, we propose a defensive dropout algorithm to determine an optimal test dropout rate given the neural network model and the attacker's strategy for generating adversarial examples. We also investigate the mechanism behind the outstanding defense effects achieved by the proposed defensive dropout.
no code implementations • NeurIPS 2018 • Yixi Xu, Xiao Wang
This paper presents a general framework for norm-based capacity control for $L_{p, q}$ weight normalized deep neural networks.
no code implementations • 25 Nov 2018 • Xiao Wang, Chenglong Li, Rui Yang, Tianzhu Zhang, Jin Tang, Bin Luo
To refine the states of the target and re-track the target when it is back to view from heavy occlusion and out of view, we elaborately design a novel subnetwork to learn the target-driven visual attentions from the guidance of both visual and natural language cues.
no code implementations • 27 Nov 2018 • Xiao Wang, Tao Sun, Rui Yang, Chenglong Li, Bin Luo, Jin Tang
In this paper, we propose an efficient quality-aware deep neural network to model the weight of data from each domain using deep reinforcement learning (DRL).
no code implementations • CVPR 2018 • Xiao Wang, Chenglong Li, Bin Luo, Jin Tang
Based on the generated hard positive samples, we train a Siamese network for visual tracking and our experiments validate the effectiveness of the introduced algorithm.
no code implementations • 6 May 2019 • Xiao Wang, Ziliang Chen, Rui Yang, Bin Luo, Jin Tang
In this paper, we propose Hard Person Identity Mining (HPIM) that attempts to refine the hard example mining to improve the exploration efficacy in person re-identification.
no code implementations • 19 Jun 2019 • Guo-Jun Qi, Liheng Zhang, Xiao Wang
Transformation Equivariant Representations (TERs) aim to capture the intrinsic visual structures that equivary to various transformations by expanding the notion of {\em translation} equivariance underlying the success of Convolutional Neural Networks (CNNs).
no code implementations • 24 Jul 2019 • Yabin Zhu, Chenglong Li, Bin Luo, Jin Tang, Xiao Wang
In different modalities, we propose to prune the densely aggregated features of all modalities in a collaborative way.
no code implementations • 25 Jul 2019 • Xiao Wang, Zhijie Wang, Yolande M. Pengetnze, Barry S. Lachman, Vikas Chowdhry
Pediatric asthma is the most prevalent chronic childhood illness, afflicting about 6. 2 million children in the United States.
no code implementations • 12 Aug 2019 • Rui Yang, Yabin Zhu, Xiao Wang, Chenglong Li, Jin Tang
RGB-Thermal object tracking attempt to locate target object using complementary visual and thermal infrared data.
no code implementations • 14 Sep 2019 • Chuan Shi, Xiaotian Han, Li Song, Xiao Wang, Senzhang Wang, Junping Du, Philip S. Yu
However, the characteristics of users and the properties of items may stem from different aspects, e. g., the brand-aspect and category-aspect of items.
no code implementations • 29 Sep 2019 • Akshay Arora, Arun Nethi, Priyanka Kharat, Vency Verghese, Grant Jenkins, Steve Miff, Vikas Chowdhry, Xiao Wang
There are multiple reasons why integrating ML models into healthcare has not been widely successful, but from a technical perspective, general-purpose commercial machine learning platforms are not a good fit for healthcare due to complexities in handling data quality issues, mandates to demonstrate clinical relevance, and a lack of ability to monitor performance in a highly regulated environment with stringent security and privacy needs.
no code implementations • 14 Oct 2019 • Lixu Wang, Shichao Xu, Xiao Wang, Qi Zhu
Federated learning (FL) has recently emerged as a new form of collaborative machine learning, where a common model can be learned while keeping all the training data on local devices.
no code implementations • 26 Nov 2019 • Yanbei Liu, Xiao Wang, Shu Wu, Zhitao Xiao
In this paper, we propose a novel Independence Promoted Graph Disentangled Networks (IPGDN) to learn disentangled node representation while enhancing the independence among node representations.
no code implementations • ICLR 2020 • Vaggos Chatziafratis, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang
Motivated by our observation that the triangle waves used in Telgarsky's work contain points of period 3 - a period that is special in that it implies chaotic behavior based on the celebrated result by Li-Yorke - we proceed to give general lower bounds for the width needed to represent periodic functions as a function of the depth.
no code implementations • 13 Feb 2020 • Yixuan Qiu, Xiao Wang
We introduce a novel and efficient algorithm called the stochastic approximate gradient descent (SAGD), as an alternative to the stochastic gradient descent for cases where unbiased stochastic gradients cannot be trivially obtained.
no code implementations • 17 Feb 2020 • Qi Lei, Sai Ganesh Nagarajan, Ioannis Panageas, Xiao Wang
In a recent series of papers it has been established that variants of Gradient Descent/Ascent and Mirror Descent exhibit last iterate convergence in convex-concave zero-sum games.
no code implementations • 18 Feb 2020 • Xiao Wang, Siyue Wang, Pin-Yu Chen, Xue Lin, Peter Chin
Recent study of adversarial attacks has revealed the vulnerability of modern deep learning models.
no code implementations • 19 Feb 2020 • Xiao Wang, Siyue Wang, Pin-Yu Chen, Xue Lin, Peter Chin
Designing effective defense against adversarial attacks is a crucial topic as deep neural networks have been proliferated rapidly in many security-critical domains such as malware detection and self-driving cars.
no code implementations • 26 Feb 2020 • Ioannis Panageas, Stratis Skoulakis, Antonios Varvitsiotis, Xiao Wang
Non-negative matrix factorization (NMF) is a fundamental non-convex optimization problem with numerous applications in Machine Learning (music analysis, document clustering, speech-source separation etc).
no code implementations • 1 Mar 2020 • Sulan Zhai, Shunqiang Liu, Xiao Wang, Jin Tang
Person search is to detect all persons and identify the query persons from detected persons in the image without proposals and bounding boxes, which is different from person re-identification.
1 code implementation • 29 Jun 2020 • Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang
Most of existing clustering algorithms are proposed without considering the selection bias in data.
no code implementations • 1 Jul 2020 • Xiao Wang, Saasha Nair, Matthias Althoff
Robust adversarial RL (RARL) was previously proposed to train an adversarial network that applies disturbances to a system, which improves the robustness in test scenarios.
no code implementations • 5 Jul 2020 • Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei
We tackle the challenge and propose an adaptive multi-channel graph convolutional networks for semi-supervised classification (AM-GCN).
no code implementations • 15 Jul 2020 • Xiao Wang, Craig Macdonald, Iadh Ounis
Query reformulations have long been a key mechanism to alleviate the vocabulary-mismatch problem in information retrieval, for example by expanding the queries with related query terms or by generating paraphrases of the queries.
no code implementations • 23 Nov 2017 • Peng Cui, Xiao Wang, Jian Pei, Wenwu Zhu
Network embedding assigns nodes in a network to low-dimensional representations and effectively preserves the network structure.
Social and Information Networks
no code implementations • 2 Sep 2020 • Jinghan Shi, Houye Ji, Chuan Shi, Xiao Wang, Zhiqiang Zhang, Jun Zhou
The prosperous development of e-commerce has spawned diverse recommendation systems.
no code implementations • 22 Sep 2020 • Weishan Zhang, Tao Zhou, Qinghua Lu, Xiao Wang, Chunsheng Zhu, Haoyun Sun, Zhipeng Wang, Sin Kit Lo, Fei-Yue Wang
To improve communication efficiency and model performance, in this paper, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections.
no code implementations • 1 Jan 2021 • Xiaoshuang Li, Junchen Jin, Xiao Wang, Fei-Yue Wang
This study proposes a novel approach integrating deep Q learning from dynamic demonstrations with a behavioral cloning model (DQfDD-BC), which includes a supervised learning technique of instructing a DRL model to enhance its performance.
no code implementations • 29 Nov 2019 • Jing Xiao, Hualin Zhan, Zaiquan Xu, Xiao Wang, Ke Zhang, Zhiyuan Xiong, George P. Simon, Zhe Liu, Dan Li
Multilayered graphene-based nanoporous membranes with electrolyte incorporated between individual sheets is a unique nano-heterostructure system in which nanoconfined electrons in graphene and ions confined in between sheets are intimately coupled throughout the entire membrane.
Mesoscale and Nanoscale Physics Materials Science Soft Condensed Matter Applied Physics Chemical Physics
no code implementations • NeurIPS 2020 • Xiao Wang, Qi Lei, Ioannis Panageas
Sampling is a fundamental and arguably very important task with numerous applications in Machine Learning.
1 code implementation • COLING 2020 • Jiapeng Liu, Xiao Zhang, Dan Goldwasser, Xiao Wang
Cross-lingual document search is an information retrieval task in which the queries' language differs from the documents' language.
no code implementations • 30 Nov 2020 • Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Philip S. Yu
Heterogeneous graphs (HGs) also known as heterogeneous information networks have become ubiquitous in real-world scenarios; therefore, HG embedding, which aims to learn representations in a lower-dimension space while preserving the heterogeneous structures and semantics for downstream tasks (e. g., node/graph classification, node clustering, link prediction), has drawn considerable attentions in recent years.
no code implementations • 9 Oct 2018 • Xiujun Cheng, Hui Wang, Xiao Wang, Jinqiao Duan, Xiaofan Li
We especially examine those most probable trajectories from low concentration state to high concentration state (i. e., the likely transcription regime) for certain parameters, in order to gain insights into the transcription processes and the tipping time for the transcription likely to occur.
no code implementations • 26 Jan 2020 • Xiao Wang, Robert D. MacDougall, Peng Chen, Charles A. Bouman, Simon K. Warfield
Our algorithm uses precise physics models to reconstruct from the native cone-beam geometry and interleaved dual source helical trajectory of a DS-FFS CT. To do so, we construct a noise physics model to represent data acquisition noise and a prior image model to represent image noise and texture.
no code implementations • 15 Apr 2021 • Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song
We also find that the performance of some hyperbolic GCNs can be improved by simply replacing the graph operations with those we defined in this paper.
no code implementations • 16 May 2021 • Xiao Wang, Wei Jiang, Wei Wang, Shan Liu, Brian Kulis, Peter Chin
The key idea is to replace the image to be compressed with a substitutional one that outperforms the original one in a desired way.
no code implementations • 14 May 2021 • Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin
This paper proposes Characteristic Examples for effectively fingerprinting deep neural networks, featuring high-robustness to the base model against model pruning as well as low-transferability to unassociated models.
no code implementations • 21 May 2021 • Yingxia Jiao, Xiao Wang, Yu-Cheng Chou, Shouyuan Yang, Ge-Peng Ji, Rong Zhu, Ge Gao
Owing to the difficulties of mining spatial-temporal cues, the existing approaches for video salient object detection (VSOD) are limited in understanding complex and noisy scenarios, and often fail in inferring prominent objects.
no code implementations • 8 Sep 2021 • Georgios Piliouras, Xiao Wang
Several recent works in online optimization and game dynamics have established strong negative complexity results including the formal emergence of instability and chaos even in small such settings, e. g., $2\times 2$ games.
no code implementations • 13 Sep 2021 • Yao Chen, Qingyi Gao, Xiao Wang
The Wasserstein GAN (WGAN) leverages the Wasserstein distance to avoid the caveats in the minmax two-player training of GANs but has other defects such as mode collapse and lack of metric to detect the convergence.
no code implementations • ICCV 2021 • Lin Zhu, Jianing Li, Xiao Wang, Tiejun Huang, Yonghong Tian
In this paper, we propose a NeuSpike-Net to learn both the high dynamic range and high motion sensitivity of DVS and the full texture sampling of spike camera to achieve high-speed and high dynamic image reconstruction.
no code implementations • 25 Sep 2019 • Jungeum Kim, Xiao Wang
The trade-off between robustness and standard accuracy has been consistently reported in the machine learning literature.
no code implementations • 25 Sep 2019 • Yao Chen, Qingyi Gao, Xiao Wang
We further provide a rigorous probabilistic interpretation of our model under the framework of maximum likelihood estimation.
no code implementations • 25 Sep 2019 • Hao Chen, Zhanfeng Mo, Qingyi Gao, Zhouwang Yang, Xiao Wang
To better understand the unsupervised model, GANs, we establish the generalization bound, which uniformly holds with respect to the choice of generators.
no code implementations • 25 Sep 2019 • Cheng Peng, Hao Wang, Xiao Wang, Zhouwang Yang
Generative Adversarial Networks (GANs) are powerful, but difficult to understand and train because GANs is a min-max problem.
no code implementations • 2 Dec 2021 • Xixi Wang, Xiao Wang, Bo Jiang, Jin Tang, Bin Luo
In this work, we re-think Transformer and extend it to MutualFormer for multi-modality data representation.
no code implementations • 19 Jan 2022 • Shaohua Fan, Xiao Wang, Chuan Shi, Kun Kuang, Nian Liu, Bai Wang
Then to remove the bias in GNN estimation, we propose a novel Debiased Graph Neural Networks (DGNN) with a differentiated decorrelation regularizer.
no code implementations • 7 Mar 2022 • Peipei Zhu, Xiao Wang, Yong Luo, Zhenglong Sun, Wei-Shi Zheng, YaoWei Wang, Changwen Chen
The image-level labels are utilized to train a weakly-supervised object recognition model to extract object information (e. g., instance) in an image, and the extracted instances are adopted to infer the relationships among different objects based on an enhanced graph neural network (GNN).
no code implementations • 18 Mar 2022 • Ilja Gubins, Marten L. Chaillet, Gijs van der Schot, M. Cristina Trueba, Remco C. Veltkamp, Friedrich Förster, Xiao Wang, Daisuke Kihara, Emmanuel Moebel, Nguyen P. Nguyen, Tommi White, Filiz Bunyak, Giorgos Papoulias, Stavros Gerolymatos, Evangelia I. Zacharaki, Konstantinos Moustakas, Xiangrui Zeng, Sinuo Liu, Min Xu, Yaoyu Wang, Cheng Chen, Xuefeng Cui, Fa Zhang
To promote innovation in computational methods, we generate a novel simulated dataset to benchmark different methods of localization and classification of biological macromolecules in tomograms.
no code implementations • 25 Apr 2022 • Yi Feng, Ioannis Panageas, Xiao Wang
We consider non-convex optimization problems with constraint that is a product of simplices.
no code implementations • 13 May 2022 • Hanna Krasowski, Jakob Thumm, Marlon Müller, Lukas Schäfer, Xiao Wang, Matthias Althoff
We categorize the methods based on how they adapt the action: action replacement, action projection, and action masking.
no code implementations • 12 May 2022 • Xiao Wang, Aristeidis Tsaris, Debangshu Mukherjee, Mohamed Wahib, Peng Chen, Mark Oxley, Olga Ovchinnikova, Jacob Hinkle
In this paper, we propose a novel image gradient decomposition method that significantly reduces the memory footprint for ptychographic reconstruction by tessellating image gradients and diffraction measurements into tiles.
1 code implementation • 20 May 2022 • Jungeum Kim, Xiao Wang
Specifically, we define a sensible adversary which is useful for learning a robust model while keeping high natural accuracy.
no code implementations • 26 May 2022 • Peipei Zhu, Xiao Wang, Lin Zhu, Zhenglong Sun, Weishi Zheng, YaoWei Wang, Changwen Chen
Inspired by the success of Vision-Language Pre-Trained Models (VL-PTMs) in this research, we attempt to infer the cross-domain cue information about a given image from the large VL-PTMs for the UIC task.
no code implementations • 26 Aug 2022 • Xixi Wang, Xiao Wang, Bo Jiang, Bin Luo
sampleFormer aims to capture the dependence of samples in support and query sets for image representation.
no code implementations • 19 Oct 2022 • Niklas Kochdumper, Hanna Krasowski, Xiao Wang, Stanley Bak, Matthias Althoff
While reinforcement learning produces very promising results for many applications, its main disadvantage is the lack of safety guarantees, which prevents its use in safety-critical systems.
no code implementations • 19 Nov 2022 • Xixi Wang, Bo Jiang, Xiao Wang, Bin Luo
(1) It employs a flexible graph model, termed Batch Graph to jointly encode the visual and semantic relationships of samples within each mini-batch.
no code implementations • 23 Nov 2022 • Adam Dziedzic, Christopher A Choquette-Choo, Natalie Dullerud, Vinith Menon Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
We use our mechanisms to enable privacy-preserving multi-label learning in the central setting by extending the canonical single-label technique: PATE.
no code implementations • 8 Feb 2023 • Yingzhou Lu, Minjie Shen, Huazheng Wang, Xiao Wang, Capucine van Rechem, Wenqi Wei
In light of these challenges, the concept of synthetic data generation emerges as a promising alternative that allows for data sharing and utilization in ways that real-world data cannot facilitate.
no code implementations • 11 Feb 2023 • Deyu Bo, Xiao Wang, Yang Liu, Yuan Fang, Yawen Li, Chuan Shi
Graph neural networks (GNNs) have attracted considerable attention from the research community.
no code implementations • 26 Mar 2023 • Yabin Zhu, Chenglong Li, Xiao Wang, Jin Tang, Zhixiang Huang
In addition, existing learning methods of RGBT trackers either fuse multimodal features into one for final classification, or exploit the relationship between unimodal branches and fused branch through a competitive learning strategy.
no code implementations • 24 Apr 2023 • Nian Liu, Xiao Wang, Hui Han, Chuan Shi
Specifically, two views of a HIN (network schema and meta-path views) are proposed to learn node embeddings, so as to capture both of local and high-order structures simultaneously.
no code implementations • 8 May 2023 • Yupei Lin, Sen Zhang, Xiaojun Yang, Xiao Wang, Yukai Shi
To ensure consistent preservation of the shape during image editing, we propose cross-attention guidance based on regeneration learning.
no code implementations • 30 May 2023 • Bo Jiang, Shuxian Luo, Xiao Wang, Chuanfu Li, Jin Tang
Second, AMatFormer adopts a shared FFN module to further embed the features of two images into the common domain and thus learn the consensus feature representations for the matching problem.
no code implementations • 1 Aug 2023 • Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis
GenQR directly reformulates the user's input query, while GenPRF provides additional context for the query by making use of pseudo-relevance feedback information.
no code implementations • 27 Aug 2023 • Xiujun Shu, Wei Wen, Liangsheng Xu, Mingbao Lin, Ruizhi Qiao, Taian Guo, Hanjun Li, Bei Gan, Xiao Wang, Xing Sun
In this paper, we present a unified and dynamic graph (UniDG) framework for temporal character grouping.
no code implementations • 31 Aug 2023 • Xiao Wang, Fang Dai, Wenyan Guo, Junfeng Wang
Therefore, a stochastic block model that integrates betweenness centrality and clustering coefficient of nodes for community detection in attributed networks, named BCSBM, is proposed in this paper.
no code implementations • 4 Oct 2023 • Xianjun Yang, Xiao Wang, Qi Zhang, Linda Petzold, William Yang Wang, Xun Zhao, Dahua Lin
This study serves as a clarion call for a collective effort to overhaul and fortify the safety of open-source LLMs against malicious attackers.
no code implementations • 6 Oct 2023 • Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael Irvin, J. Gregory Pauloski, Logan Ward, Valerie Hayot, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian Foster, James J. Davis, Michael E. Papka, Thomas Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi Hanson, Thomas E Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin Aji, Angela Dalton, Michael Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences.
no code implementations • 18 Oct 2023 • Rui Zheng, Wei Shen, Yuan Hua, Wenbin Lai, Shihan Dou, Yuhao Zhou, Zhiheng Xi, Xiao Wang, Haoran Huang, Tao Gui, Qi Zhang, Xuanjing Huang
In this work, we propose a novel approach that can learn a consistent policy via RL across various data groups or domains.
no code implementations • 4 Nov 2023 • Xiao Wang, Isaac Lyngaas, Aristeidis Tsaris, Peng Chen, Sajal Dash, Mayanka Chandra Shekar, Tao Luo, Hong-Jun Yoon, Mohamed Wahib, John Gouley
This paper presents a novel and efficient distributed training method, the Long Short-Sequence Transformer (LSS Transformer), for training transformer with long sequences.
no code implementations • 14 Dec 2023 • Yibo Li, Xiao Wang, Hongrui Liu, Chuan Shi
In this paper, we propose a general diffusion equation framework with the fidelity term, which formally establishes the relationship between the diffusion process with more GNNs.
no code implementations • 20 Dec 2023 • Sajal Dash, Isaac Lyngaas, Junqi Yin, Xiao Wang, Romain Egele, Guojing Cong, Feiyi Wang, Prasanna Balaprakash
For the training of the 175 Billion parameter model and the 1 Trillion parameter model, we achieved $100\%$ weak scaling efficiency on 1024 and 3072 MI250X GPUs, respectively.
no code implementations • 21 Dec 2023 • Lixu Wang, Chenxi Liu, Junfeng Guo, Jiahua Dong, Xiao Wang, Heng Huang, Qi Zhu
In a privacy-focused era, Federated Learning (FL) has emerged as a promising machine learning technique.
no code implementations • 30 Jan 2024 • Linyao Yang, Hongyang Chen, Xiao Wang, Jing Yang, Fei-Yue Wang, Han Liu
The final prediction of the equivalent entity is derived from the LLM's output.