1 code implementation • EMNLP 2021 • Haoran Ding, Xiao Luo
The self-attention is designed to determine the importance of a candidate within the context of a sentence.
1 code implementation • 13 Mar 2024 • Weikai Li, Zhiping Xiao, Xiao Luo, Yizhou Sun
We propose a new method of evaluating node influence, which measures the prediction change of a trained GNN model caused by removing a node.
no code implementations • 7 Mar 2024 • Wei Ju, Siyu Yi, Yifan Wang, Zhiping Xiao, Zhengyang Mao, Hourun Li, Yiyang Gu, Yifang Qin, Nan Yin, Senzhang Wang, Xinwang Liu, Xiao Luo, Philip S. Yu, Ming Zhang
To tackle these issues, substantial efforts have been devoted to improving the performance of GNN models in practical real-world scenarios, as well as enhancing their reliability and robustness.
no code implementations • 2 Mar 2024 • Wei Ju, Yusheng Zhao, Yifang Qin, Siyu Yi, Jingyang Yuan, Zhiping Xiao, Xiao Luo, Xiting Yan, Ming Zhang
Toward this end, this paper proposes Conjoint Spatio-Temporal graph neural network (abbreviated as COOL), which models heterogeneous graphs from prior and posterior information to conjointly capture high-order spatio-temporal relationships.
no code implementations • 26 Feb 2024 • Yihang Zhou, Qingqing Long, Yuchen Yan, Xiao Luo, Zeyu Dong, Xuezhi Wang, Zhen Meng, Pengfei Wang, Yuanchun Zhou
Zero-shot hashing (ZSH) has shown excellent success owing to its efficiency and generalization in large-scale retrieval scenarios.
no code implementations • 21 Feb 2024 • Hengchuang Yin, Zhonghui Gu, Fanhao Wang, Yiparemu Abuduhaibaier, Yanqiao Zhu, Xinming Tu, Xian-Sheng Hua, Xiao Luo, Yizhou Sun
Large language models (LLMs) such as ChatGPT have gained considerable interest across diverse research communities.
no code implementations • 29 Jan 2024 • Wei Ju, Yiyang Gu, Zhengyang Mao, Ziyue Qiao, Yifang Qin, Xiao Luo, Hui Xiong, Ming Zhang
Self-supervised graph representation learning has recently shown considerable promise in a range of fields, including bioinformatics and social networks.
no code implementations • 23 Jan 2024 • Yifang Qin, Wei Ju, Xiao Luo, Yiyang Gu, Zhiping Xiao, Ming Zhang
Collaborative Filtering (CF) is a pivotal research area in recommender systems that capitalizes on collaborative similarities between users and items to provide personalized recommendations.
no code implementations • 1 Jan 2024 • Hourun Li, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Zhiping Xiao, Jiaqi Feng, Yiyang Gu, Wei Ju, Xiao Luo, Ming Zhang
However, most of the research in this area is still concentrated on traffic forecasting, while other ITS domains, such as autonomous vehicles and urban planning, still require more attention.
1 code implementation • 21 Dec 2023 • Behafarid Mohammad Jafari, Xiao Luo, Ali Jafari
Social recommendations have been widely adopted in substantial domains.
no code implementations • 11 Nov 2023 • Xiao Luo, Yiyang Gu, Huiyu Jiang, Jinsheng Huang, Wei Ju, Ming Zhang, Yizhou Sun
In this paper, we propose a new approach named Graph ODE with factorized prototypes (GOAT) to address the problem.
no code implementations • 10 Oct 2023 • Zijie Huang, Wanjia Zhao, Jingdong Gao, Ziniu Hu, Xiao Luo, Yadi Cao, Yuanzhou Chen, Yizhou Sun, Wei Wang
Learning complex multi-agent system dynamics from data is crucial across many domains, such as in physical simulations and material modeling.
no code implementations • 3 Oct 2023 • Yijia Xiao, Yiqiao Jin, Yushi Bai, Yue Wu, Xianjun Yang, Xiao Luo, Wenchao Yu, Xujiang Zhao, Yanchi Liu, Haifeng Chen, Wei Wang, Wei Cheng
To address this challenge, we introduce Privacy Protection Language Models (PPLM), a novel paradigm for fine-tuning LLMs that effectively injects domain-specific knowledge while safeguarding data privacy.
no code implementations • 26 Sep 2023 • Jingyang Yuan, Xiao Luo, Yifang Qin, Zhengyang Mao, Wei Ju, Ming Zhang
Nevertheless, the majority of GNN-based approaches have been examined using well-annotated benchmark datasets, leading to suboptimal performance in real-world graph learning scenarios.
no code implementations • 21 Sep 2023 • Yusheng Zhao, Xiao Luo, Wei Ju, Chong Chen, Xian-Sheng Hua, Ming Zhang
This paper studies the problem of traffic flow forecasting, which aims to predict future traffic conditions on the basis of road networks and traffic conditions in the past.
no code implementations • 19 Sep 2023 • Ziyue Qiao, Xiao Luo, Meng Xiao, Hao Dong, Yuanchun Zhou, Hui Xiong
To deal with the domain shift, we add adaptive shift parameters to each of the source nodes, which are trained in an adversarial manner to align the cross-domain distributions of node embedding, thus the node classifier trained on labeled source nodes can be transferred to the target nodes.
no code implementations • 11 Sep 2023 • Neel Bhate, Ansh Mittal, Zhe He, Xiao Luo
We utilize de-identified real-world clinical notes annotated for demographics, various social determinants, and family history information.
1 code implementation • 9 Sep 2023 • Si-Yu Yi, Wei Ju, Yifang Qin, Xiao Luo, Luchen Liu, Yong-Dao Zhou, Ming Zhang
Graph clustering, which learns the node representations for effective cluster assignments, is a fundamental yet challenging task in data analysis and has received considerable attention accompanied by graph neural networks in recent years.
no code implementations • 31 Aug 2023 • Siyu Yi, Zhengyang Mao, Wei Ju, Yongdao Zhou, Luchen Liu, Xiao Luo, Ming Zhang
Graph classification, aiming at learning the graph-level representations for effective class assignments, has received outstanding achievements, which heavily relies on high-quality datasets that have balanced class distribution.
no code implementations • 4 Aug 2023 • Zhengyang Mao, Wei Ju, Yifang Qin, Xiao Luo, Ming Zhang
Recent approaches mainly focus on re-balancing different classes during model training, which fails to explicitly introduce new knowledge and sacrifices the performance of the head classes.
2 code implementations • 27 Jul 2023 • Zhen Qin, Dong Li, Weigao Sun, Weixuan Sun, Xuyang Shen, Xiaodong Han, Yunshen Wei, Baohong Lv, Xiao Luo, Yu Qiao, Yiran Zhong
TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization.
no code implementations • 20 Jun 2023 • Song Jiang, Zijie Huang, Xiao Luo, Yizhou Sun
We model a multi-agent dynamical system as a graph and propose CounterFactual GraphODE (CF-GODE), a causal model that estimates continuous-time counterfactual outcomes in the presence of inter-dependencies between units.
no code implementations • 14 Jun 2023 • Jingyang Yuan, Xiao Luo, Yifang Qin, Yusheng Zhao, Wei Ju, Ming Zhang
Since this regularization term cannot utilize label information, it can enhance the robustness of node representations to label noise.
no code implementations • 8 Jun 2023 • Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian-Sheng Hua, Xiao Luo
Although graph neural networks (GNNs) have achieved impressive achievements in graph classification, they often need abundant task-specific labels, which could be extensively costly to acquire.
no code implementations • 2 Jun 2023 • Jinjin Cai, Sudip Vhaduri, Xiao Luo
Rapid discovery of new diseases, such as COVID-19 can enable a timely epidemic response, preventing the large-scale spread and protecting public health.
no code implementations • 31 May 2023 • Xiao Luo, Yusheng Zhao, Yifang Qin, Wei Ju, Ming Zhang
To tackle class shifts, we estimate the certainty of unlabeled graphs using multiple subgraphs, which facilities the discovery of unlabeled data from unknown categories.
1 code implementation • 19 May 2023 • Hao Wu, Wei Xiong, Fan Xu, Xiao Luo, Chong Chen, Xian-Sheng Hua, Haixin Wang
In this paper, we investigate the challenge of spatio-temporal video prediction, which involves generating future videos based on historical data streams.
no code implementations • 23 Apr 2023 • Wei Ju, Xiao Luo, Meng Qu, Yifan Wang, Chong Chen, Minghua Deng, Xian-Sheng Hua, Ming Zhang
The two twin modules collaborate with each other by exchanging instance similarity knowledge to fully explore the structure information of both labeled and unlabeled data.
1 code implementation • 14 Apr 2023 • Yifang Qin, Hongjun Wu, Wei Ju, Xiao Luo, Ming Zhang
In this paper, we propose Diff-POI: a Diffusion-based model that samples the user's spatial preference for the next POI recommendation.
no code implementations • 14 Apr 2023 • Yifang Qin, Wei Ju, Hongjun Wu, Xiao Luo, Ming Zhang
Technically, GDERec is characterized by an autoregressive graph ordinary differential equation consisting of two components, which are parameterized by two tailored graph neural networks (GNNs) respectively to capture user preference from the perspective of hybrid dynamical systems.
no code implementations • 11 Apr 2023 • Wei Ju, Zheng Fang, Yiyang Gu, Zequn Liu, Qingqing Long, Ziyue Qiao, Yifang Qin, Jianhao Shen, Fang Sun, Zhiping Xiao, Junwei Yang, Jingyang Yuan, Yusheng Zhao, Yifan Wang, Xiao Luo, Ming Zhang
Graph representation learning aims to effectively encode high-dimensional sparse graph-structured data into low-dimensional dense vectors, which is a fundamental task that has been widely studied in a range of fields, including machine learning and data mining.
no code implementations • 17 Mar 2023 • Haixin Wang, Jianlong Chang, Xiao Luo, Jinan Sun, Zhouchen Lin, Qi Tian
Despite recent competitive performance across a range of vision tasks, vision Transformers still have an issue of heavy computational costs.
no code implementations • ICCV 2023 • Xinlong Yang, Haixin Wang, Jinan Sun, Shikun Zhang, Chong Chen, Xian-Sheng Hua, Xiao Luo
This paper investigates a realistic but understudied problem of image retrieval under label noise, which could lead to severe overfitting or memorization of noisy samples during optimization.
no code implementations • 21 Oct 2022 • Wei Ju, Yiyang Gu, Binqi Chen, Gongbo Sun, Yifang Qin, Xingyuming Liu, Xiao Luo, Ming Zhang
In this paper, we propose a general graph-level clustering framework named Graph-Level Contrastive Clustering (GLCC) given multiple graphs.
1 code implementation • 8 Oct 2022 • Wei Ju, Yifang Qin, Ziyue Qiao, Xiao Luo, Yifan Wang, Yanjie Fu, Ming Zhang
To tackle the above issues, we propose a Kernel-Based Graph Neural Network (KBGNN) for next POI recommendation, which combines the characteristics of both geographical and sequential influences in a collaborative way.
4 code implementations • 3 Oct 2022 • Weicong Liang, Yuhui Yuan, Henghui Ding, Xiao Luo, WeiHong Lin, Ding Jia, Zheng Zhang, Chao Zhang, Han Hu
Vision transformers have recently achieved competitive results across various vision tasks but still suffer from heavy computation costs when processing a large number of tokens.
no code implementations • 26 May 2022 • Yiyue Zhao, Xinyu Yun, Chen Chai, Zhiyu Liu, Wenxuan Fan, Xiao Luo
Thus, this study proposed a comprehensive and efficient textual explanation model.
no code implementations • 13 Mar 2022 • Md. Ahsanul Kabir, AlJohara Almulhim, Xiao Luo, Mohammad Al Hasan
Unfortunately, in medical literature, cause and effect phrases in a sentence are not simply nouns or noun phrases, rather they are complex phrases consisting of several words, and existing methods fail to correctly extract the cause and effect entities in such sentences.
no code implementations • 13 Sep 2021 • Daqing Wu, Xiao Luo, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma
Nowadays, E-commerce is increasingly integrated into our daily lives.
1 code implementation • 2 Jun 2021 • Yuhang Guo, Xiao Luo, Liang Chen, Minghua Deng
Predicting DNA-protein binding is an important and classic problem in bioinformatics.
1 code implementation • 25 May 2021 • Xiao Luo, Daqing Wu, Yiyang Gu, Chong Chen, Luchen Liu, Jinwen Ma, Ming Zhang, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua
Besides, CHCF integrates criterion learning and user preference learning into a unified framework, which can be trained jointly for the interaction prediction of the target behavior.
no code implementations • 13 May 2021 • Xiao Luo, Zeyu Ma, Daqing Wu, Huasong Zhong, Chong Chen, Jinwen Ma, Minghua Deng
Hashing has been widely used in approximate nearest neighbor search for its storage and computational efficiency.
no code implementations • 4 Apr 2021 • Md. Ahsanul Kabir, Typer Phillips, Xiao Luo, Mohammad Al Hasan
Semantic relationships, such as hyponym-hypernym, cause-effect, meronym-holonym etc.
no code implementations • 15 Oct 2020 • Xiao Luo, Daqing Wu, Zeyu Ma, Chong Chen, Minghua Deng, Jinwen Ma, Zhongming Jin, Jianqiang Huang, Xian-Sheng Hua
However, due to the inefficient representation ability of the pre-trained model, many false positives and negatives in local semantic similarity will be introduced and lead to error propagation during the hash code learning.
no code implementations • 4 Mar 2020 • Xiao Luo, Haixin Wang, Daqing Wu, Chong Chen, Minghua Deng, Jianqiang Huang, Xian-Sheng Hua
Nearest neighbor search aims to obtain the samples in the database with the smallest distances from them to the queries, which is a basic task in a range of fields, including computer vision and data mining.
no code implementations • 13 Oct 2019 • Matthew Tang, Priyanka Gandhi, Md Ahsanul Kabir, Christopher Zou, Jordyn Blakey, Xiao Luo
The attention-based models in this research are capable of presenting the human interpretable text classification models.
no code implementations • 18 Apr 2019 • Tien Huu Do, Xiao Luo, Duc Minh Nguyen, Nikos Deligiannis
Many methods have been introduced to detect rumours using the content or the social context of news.
no code implementations • 22 Oct 2018 • Setu Shah, Xiao Luo
In this research, a vector representation of concepts of diseases and similarity measurement between concepts are proposed.