1 code implementation • 20 Nov 2024 • Yuan Yuan, Jingtao Ding, Chonghua Han, Depeng Jin, Yong Li
In this paper, we build UniFlow, a foundational model for general urban flow prediction that unifies both grid-based and graphbased data.
1 code implementation • 19 Nov 2024 • Yuan Yuan, Chonghua Han, Jingtao Ding, Depeng Jin, Yong Li
This allows the model to unify both multi-data and multi-task learning, and effectively support a wide range of spatio-temporal applications.
1 code implementation • 4 Nov 2024 • Lei Chen, Chen Gao, Xiaoyi Du, Hengliang Luo, Depeng Jin, Yong Li, Meng Wang
The basic idea of LLM4IDRec is that by employing LLM to augment ID data, if augmented ID data can improve recommendation performance, it demonstrates the ability of LLM to interpret ID data effectively, exploring an innovative way for the integration of LLM in ID-based recommendation.
no code implementations • 29 Oct 2024 • Zhilun Zhou, Jingyang Fan, Yu Liu, Fengli Xu, Depeng Jin, Yong Li
Motivated by the remarkable abilities of large language models (LLMs) in commonsense reasoning, embedding, and multi-agent collaboration, in this work, we synergize LLM agents and knowledge graph for socioeconomic prediction.
no code implementations • 3 Sep 2024 • Hongyuan Su, Yu Zheng, Jingtao Ding, Depeng Jin, Yong Li
The facility location problem (FLP) is a classical combinatorial optimization challenge aimed at strategically laying out facilities to maximize their accessibility.
1 code implementation • 23 Jul 2024 • Huandong Wang, Changzheng Gao, Yuchen Wu, Depeng Jin, Lina Yao, Yong Li
In the training process, only the generated trajectories and their rewards obtained based on personal discriminators are shared between the server and devices, whose privacy is further preserved by our proposed perturbation mechanisms with theoretical proof to satisfy differential privacy.
1 code implementation • 15 Jun 2024 • Jun Zhang, Wenxuan Ao, Junbo Yan, Depeng Jin, Yong Li
However, existing microscopic traffic simulators are inefficient in large-scale scenarios and thus fail to support the adoption of these methods in large-scale transportation system optimization scenarios.
no code implementations • 27 Feb 2024 • Zhilun Zhou, Yuming Lin, Depeng Jin, Yong Li
To deal with the different facilities needs of residents, we initiate a discussion among the residents in each community about the plan, where residents provide feedback based on their profiles.
1 code implementation • 19 Feb 2024 • Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li
Urban spatio-temporal prediction is crucial for informed decision-making, such as traffic management, resource optimization, and emergence response.
1 code implementation • 19 Feb 2024 • Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li
Spatio-temporal modeling is foundational for smart city applications, yet it is often hindered by data scarcity in many cities and regions.
1 code implementation • 14 Nov 2023 • GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang
Recent proposed cross-domain sequential recommendation models such as PiNet and DASL have a common drawback relying heavily on overlapped users in different domains, which limits their usage in practical recommender systems.
1 code implementation • 14 Nov 2023 • GuanYu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li
In this paper, we propose a meta-learning method to annotate the unlabeled data from loss and gradient perspectives, which considers the noises in both positive and negative instances.
1 code implementation • 16 Oct 2023 • Xiaochong Lan, Chen Gao, Depeng Jin, Yong Li
Next, in the reasoning-enhanced debating stage, for each potential stance, we designate a specific LLM-based agent to advocate for it, guiding the LLM to detect logical connections between text features and stance, tackling the second challenge.
Ranked #1 on
Stance Detection
on P-Stance
no code implementations • 13 Oct 2023 • Zhenyu Han, Qianyue Hao, Qiwei He, Katherine Budeski, Depeng Jin, Fengli Xu, Kun Tang
We explore the possibility of the enlightened self-interest incentive mechanism, i. e., improving one's own epidemic outcomes by sharing vaccines with other countries, by evaluating the number of infections and deaths under various vaccine sharing strategies using the proposed model.
1 code implementation • 19 Sep 2023 • Zhilun Zhou, Jingtao Ding, Yu Liu, Depeng Jin, Yong Li
To capture the effect of multiple factors on urban flow, such as region features and urban environment, we employ diffusion model to generate urban flow for regions under different conditions.
no code implementations • 28 Aug 2023 • Yuhan Quan, Jingtao Ding, Chen Gao, Nian Li, Lingling Yi, Depeng Jin, Yong Li
Micro-videos platforms such as TikTok are extremely popular nowadays.
no code implementations • 25 Aug 2023 • Yunzhu Pan, Nian Li, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Depeng Jin, Yong Li
Specifically, in short-video recommendation, the easiest-to-collect user feedback is the skipping behavior, which leads to two critical challenges for the recommendation model.
1 code implementation • 8 Aug 2023 • Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Depeng Jin, Yong Li
To enhance the robustness of our model, we then introduce a multi-task learning module to simultaneously optimize two kinds of feedback -- passive-negative feedback and traditional randomly-sampled negative feedback.
no code implementations • 7 Aug 2023 • Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin, Yong Li
Graph Neural Network (GNN)-based models have become the mainstream approach for recommender systems.
1 code implementation • 19 Jul 2023 • Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li
Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist naturally in the form of networks, is of great value to us.
no code implementations • 17 Jun 2023 • Huandong Wang, Huan Yan, Can Rong, Yuan Yuan, Fenyu Jiang, Zhenyu Han, Hongjie Sui, Depeng Jin, Yong Li
In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data.
no code implementations • 14 Jun 2023 • Tong Li, Li Yu, Yibo Ma, Tong Duan, Wenzhen Huang, Yan Zhou, Depeng Jin, Yong Li, Tao Jiang
We show that the decline in carbon efficiency leads to a carbon efficiency trap, estimated to cause additional carbon emissions of 23. 82 +- 1. 07 megatons in China.
1 code implementation • 22 May 2023 • Yu Zheng, Hongyuan Su, Jingtao Ding, Depeng Jin, Yong Li
Existing re-blocking or heuristic methods are either time-consuming which cannot generalize to different slums, or yield sub-optimal road plans in terms of accessibility and construction costs.
2 code implementations • 21 May 2023 • Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, Yong Li
To enhance the learning of each step, an elaborated spatio-temporal co-attention module is proposed to capture the interdependence between the event time and space adaptively.
1 code implementation • 15 Mar 2023 • Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li
Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in social relations.
no code implementations • 22 Feb 2023 • Huiming Chen, Huandong Wang, Qingyue Long, Depeng Jin, Yong Li
Based on these frameworks, we have instantiated FedOpt algorithms.
1 code implementation • 9 Feb 2023 • Yuan Yuan, Huandong Wang, Jingtao Ding, Depeng Jin, Yong Li
To enhance the fidelity and utility of the generated activity data, our core idea is to model the evolution of human needs as the underlying mechanism that drives activity generation in the simulation model.
1 code implementation • 8 Feb 2023 • GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Zhiheng Li, Depeng Jin, Yong Li
In this paper, we propose Dual-interest Factorization-heads Attention for Sequential Recommendation (short for DFAR) consisting of feedback-aware encoding layer, dual-interest disentangling layer and prediction layer.
no code implementations • AAAI -22 2022 • Zefang Zong, Meng Zheng, Yong Li, Depeng Jin
It is of great importance to efficiently provide high-quality solutions of cooperative PDP.
1 code implementation • 18 Sep 2022 • GuanYu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin, Dong Li, Jianye Hao, Yong Li
Such user-centric recommendation will make it impossible for the provider to expose their new items, failing to consider the accordant interactions between user and item dimensions.
1 code implementation • 14 Aug 2022 • Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li
In particular, we first unify the fine-grained user similarity and the complex matching between user preferences and spatiotemporal activity into a heterogeneous hypergraph.
1 code implementation • 10 Aug 2022 • Yu Zheng, Chen Gao, Jingtao Ding, Lingling Yi, Depeng Jin, Yong Li, Meng Wang
Recommender systems are prone to be misled by biases in the data.
1 code implementation • 26 Feb 2022 • Yu Zheng, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Depeng Jin, Yong Li
Modeling user's long-term and short-term interests is crucial for accurate recommendation.
no code implementations • 15 Dec 2021 • Huiming Chen, Huandong Wang, Quanming Yao, Yong Li, Depeng Jin, Qiang Yang
Federated optimization (FedOpt), which targets at collaboratively training a learning model across a large number of distributed clients, is vital for federated learning.
no code implementations • NeurIPS 2021 • Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li
Deep sparse networks (DSNs), of which the crux is exploring the high-order feature interactions, have become the state-of-the-art on the prediction task with high-sparsity features.
1 code implementation • 5 Nov 2021 • Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, Yong Li
With the hypergraph convolutional networks, the social relations can be modeled in a more fine-grained manner, which more accurately depicts real users' preferences, and benefits the recommendation performance.
no code implementations • 1 Nov 2021 • Huandong Wang, Qiaohong Yu, Yu Liu, Depeng Jin, Yong Li
Further, a complex embedding model with elaborately designed scoring functions is proposed to measure the plausibility of facts in STKG to solve the knowledge graph completion problem, which considers temporal dynamics of the mobility patterns and utilizes PoI categories as the auxiliary information and background knowledge.
no code implementations • 1 Nov 2021 • Chang Liu, Chen Gao, Depeng Jin, Yong Li
We first conduct information propagation on two sub-graphs to learn the representations of POIs and users.
no code implementations • submitted to TOIS 2021 • Chen Gao, Yu Zheng, Nian Li, Yinfeng Li, Yingrong Qin, Jinghua Piao, Yuhan Quan, Jianxin Chang, Depeng Jin, Xiangnan He, Yong Li
In this survey, we conduct a comprehensive review of the literature on graph neural network-based recommender systems.
2 code implementations • 16 Aug 2021 • Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li
These years much effort has been devoted to improving the accuracy or relevance of the recommendation system.
no code implementations • 10 Aug 2021 • Zefang Zong, Jingwei Wang, Tao Feng, Tong Xia, Depeng Jin, Yong Li
For each problem, we comprehensively introduce the existing DRL solutions.
1 code implementation • 27 Jun 2021 • Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang song, Depeng Jin, Yong Li
This helps explicitly distinguish users' core interests, by forming dense clusters in the interest graph.
no code implementations • 14 Jun 2021 • Chen Gao, Quanming Yao, Depeng Jin, Yong Li
In this way, we can combinatorially generalize data-specific CF models, which have not been visited in the literature, from SOTA ones.
1 code implementation • 30 Apr 2021 • Fuxian Li, Jie Feng, Huan Yan, Guangyin Jin, Depeng Jin, Yong Li
Additionally, there is a severe lack of fair comparison among different methods on the same datasets.
Ranked #2 on
Traffic Prediction
on NE-BJ
no code implementations • 21 Feb 2021 • Zhenyu Han, Fengli Xu, Yong Li, Tao Jiang, Depeng Jin, Jianhua Lu, James A. Evans
With the continued spread of coronavirus, the task of forecasting distinctive COVID-19 growth curves in different cities, which remain inadequately explained by standard epidemiological models, is critical for medical supply and treatment.
1 code implementation • ICLR 2021 • Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li
Existing works that try to address the problem always cause a significant drop in recommendation performance or suffers from the limitation of unaffordable training time cost.
no code implementations • 1 Jan 2021 • Hansen Wang, Zefang Zong, Tong Xia, Shuyu Luo, Meng Zheng, Depeng Jin, Yong Li
The large-scale vehicle routing problem is defined based on the classical VRP with usually more than one thousand customers.
1 code implementation • 14 Oct 2020 • Jun Zhang, Chen Gao, Depeng Jin, Yong Li
Group-buying recommendation for social e-commerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.
1 code implementation • NeurIPS 2020 • Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin
Negative sampling approaches are prevalent in implicit collaborative filtering for obtaining negative labels from massive unlabeled data.
3 code implementations • 19 Jun 2020 • Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, Yong Li
We further demonstrate that the learned embeddings successfully capture the desired causes, and show that DICE guarantees the robustness and interpretability of recommendation.
1 code implementation • 7 May 2020 • Jianxin Chang, Chen Gao, Xiangnan He, Yong Li, Depeng Jin
Existing solutions integrate user-item interaction modeling into bundle recommendation by sharing model parameters or learning in a multi-task manner, which cannot explicitly model the affiliation between items and bundles, and fail to explore the decision-making when a user chooses bundles.
1 code implementation • 9 Mar 2020 • Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin
Price, an important factor in marketing --- which determines whether a user will make the final purchase decision on an item --- surprisingly, has received relatively little scrutiny.
no code implementations • 3 Nov 2019 • Sirui Song, Tong Xia, Depeng Jin, Pan Hui, Yong Li
In this paper, to reveal urban dynamics, we propose a novel system UrbanRhythm to reveal the urban dynamics hidden in human mobility data.
no code implementations • 21 Sep 2018 • Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang song, Depeng Jin
To fully exploit the signal in the data of multiple types of behaviors, we perform a joint optimization based on the multi-task learning framework, where the optimization on a behavior is treated as a task.
no code implementations • 21 Feb 2017 • Fengli Xu, Zhen Tu, Yong Li, Pengyu Zhang, Xiao-Ming Fu, Depeng Jin
By conducting experiments on two real-world datasets collected from both mobile application and cellular network, we reveal that the attack system is able to recover users' trajectories with accuracy about 73%~91% at the scale of tens of thousands to hundreds of thousands users, which indicates severe privacy leakage in such datasets.
Computers and Society Cryptography and Security