1 code implementation • 10 May 2024 • Yu Lei, Haolun Luo, Lituan Wang, Zhenwei Zhang, Lei Zhang
In weakly supervised medical image segmentation, the absence of structural priors and the discreteness of class feature distribution present a challenge, i. e., how to accurately propagate supervision signals from local to global regions without excessively spreading them to other irrelevant regions?
1 code implementation • 19 Apr 2024 • Yu Lei, Zixuan Wang, Chu Liu, Tongyao Wang, Dongyang Lee
Our research demonstrates that FinLangNet surpasses traditional statistical methods in predicting credit risk and that its integration with these methods enhances credit card fraud prediction models, achieving a significant improvement of over 1. 5 points in the Kolmogorov-Smirnov metric.
no code implementations • 18 Apr 2024 • Shunpan Liang, Junjie Zhao, Chen Li, Yu Lei
This model uses relationships in the knowledge graph to construct intents, aiming to mine the connections between users' multi-behaviors from the perspective of intents to achieve more accurate recommendations.
no code implementations • 18 Apr 2024 • Xiang Li, Shunpan Liang, Yu Lei, Chen Li, Yulei Hou, Tengfei Ma
Medication recommendation systems are designed to deliver personalized drug suggestions that are closely aligned with individual patient needs.
no code implementations • 7 Apr 2024 • Yu Lei, Guoshuai Sheng, Fangfang Li, Quanxue Gao, Cheng Deng, Qin Li
However, current attention-based models may overlook the transferability of visual features and the distinctiveness of attribute localization when learning regional features in images.
no code implementations • 4 Apr 2024 • Li Xiaopeng, Zeng Zhaoyuan, Fan Cien, Zhao Chen, Deng Lei, Yu Lei
High dynamic range imaging (HDRI) for real-world dynamic scenes is challenging because moving objects may lead to hybrid degradation of low dynamic range and motion blur.
no code implementations • 11 Mar 2024 • Haiyang Xu, Yu Lei, Zeyuan Chen, Xiang Zhang, Yue Zhao, Yilin Wang, Zhuowen Tu
We present Bayesian Diffusion Models (BDM), a prediction algorithm that performs effective Bayesian inference by tightly coupling the top-down (prior) information with the bottom-up (data-driven) procedure via joint diffusion processes.
no code implementations • 4 Mar 2024 • Yuxiao Wang, Zhenao Wei, Xinyu Jiang, Yu Lei, Weiying Xue, Jinxiu Liu, Qi Liu
Recent human-object interaction (HOI) detection approaches rely on high cost of manpower and require comprehensive annotated image datasets.
no code implementations • 1 Mar 2024 • Shunpan Liang, Xiang Li, Chen Li, Yu Lei, Yulei Hou, Tengfei Ma
Medication recommendation aims to integrate patients' long-term health records with medical knowledge, recommending accuracy and safe medication combinations for specific conditions.
no code implementations • 22 Feb 2024 • Han Zhang, Lin Gui, Yu Lei, Yuanzhao Zhai, Yehong Zhang, Yulan He, Hui Wang, Yue Yu, Kam-Fai Wong, Bin Liang, Ruifeng Xu
Reinforcement Learning from Human Feedback (RLHF) is commonly utilized to improve the alignment of Large Language Models (LLMs) with human preferences.
no code implementations • Conference 2024 • Han Zhang, Yu Lei, Lin Gui, Min Yang, Yulan He, Hui Wang, Ruifeng Xu
The approach of Reinforcement Learning from Human Feedback (RLHF) is widely used for enhancing pre-trained Language Models (LM), enabling them to better align with human preferences.
no code implementations • 30 Dec 2023 • Yuanzhao Zhai, Han Zhang, Yu Lei, Yue Yu, Kele Xu, Dawei Feng, Bo Ding, Huaimin Wang
Reinforcement learning from human feedback (RLHF) emerges as a promising paradigm for aligning large language models (LLMs).
no code implementations • 24 Oct 2023 • Han Zhang, Lin Gui, Yuanzhao Zhai, Hui Wang, Yu Lei, Ruifeng Xu
The technique of Reinforcement Learning from Human Feedback (RLHF) is a commonly employed method to improve pre-trained Language Models (LM), enhancing their ability to conform to human preferences.
no code implementations • 21 Aug 2023 • Yuhan Li, Yishun Dou, Yue Shi, Yu Lei, Xuanhong Chen, Yi Zhang, Peng Zhou, Bingbing Ni
While text-3D editing has made significant strides in leveraging score distillation sampling, emerging approaches still fall short in delivering separable, precise and consistent outcomes that are vital to content creation.
1 code implementation • 12 Oct 2022 • Xiaosu Zhu, Jingkuan Song, Yu Lei, Lianli Gao, Heng Tao Shen
By testing on a series of hash-models, we obtain performance improvements among all of them, with an up to $26. 5\%$ increase in mean Average Precision and an up to $20. 5\%$ increase in accuracy.
1 code implementation • 1 Sep 2022 • Zhu Sun, Yu Lei, Lu Zhang, Chen Li, Yew-Soon Ong, Jie Zhang
Being equipped with three modules (i. e., global user behavior encoder, local multi-channel encoder, and region-aware weighting strategy), MCMG is capable of capturing both fine- and coarse-grained sequential regularities as well as exploring the dynamic impact of multi-channel by differentiating the region check-in patterns.
no code implementations • 26 Oct 2021 • Junning Liu, Zijie Xia, Yu Lei, Xinjian Li, Xu Wang
For example, when using MTL to model various user behaviors in RS, if we differentiate new users and new items from old ones, there will be a cartesian product style increase of tasks with multi-dimensional relations.
no code implementations • 18 Oct 2021 • Yu Lei, Jing Zhang
To effectively classify graph instances, graph neural networks need to have the capability to capture the part-whole relationship existing in a graph.
no code implementations • 9 Oct 2021 • Xiaolong Zheng, Deyun Zhou, Na Li, Yu Lei, Tao Wu, Maoguo Gong
In the focus search strategy, if there is no knowledge source benefit the optimization of a task, then all knowledge sources in the task's pool are forbidden to be utilized except the task, which helps to improve the performance of the proposed algorithm.
no code implementations • 13 May 2021 • Yingbo Li, Yucong Duan, Anamaria-Beatrice Spulber, Haoyang Che, Zakaria Maamar, Zhao Li, Chen Yang, Yu Lei
In this paper we explore the concept of Physicial Artifical Intelligence and propose two subdomains: Integrated Physicial Artifical Intelligence and Distributed Physicial Artifical Intelligence.
4 code implementations • ICLR 2020 • Hongbin Pei, Bingzhe Wei, Kevin Chen-Chuan Chang, Yu Lei, Bo Yang
From the observations on classical neural network and network geometry, we propose a novel geometric aggregation scheme for graph neural networks to overcome the two weaknesses.
Node Classification on Non-Homophilic (Heterophilic) Graphs Representation Learning +1
no code implementations • 2 Feb 2019 • Yu Lei, Wenjie Li
In this paper, we study a multi-step interactive recommendation problem, where the item recommended at current step may affect the quality of future recommendations.
no code implementations • 26 Apr 2018 • Jia Liu, Yu Lei, Yan Ke, Jun Li, Min-qing Zhang, Xiaoyuan Yan
In this paper, a new data-driven information hiding scheme called generative steganography by sampling (GSS) is proposed.
no code implementations • 9 Dec 2017 • Dayong Tian, Maoguo Gong, Deyun Zhou, Jiao Shi, Yu Lei
As unsupervised multimodal hashing methods are usually inferior to supervised ones, while the supervised ones requires too much manually labeled data, the proposed method in this paper utilizes a part of labels to design a semi-supervised multimodal hashing method.
no code implementations • COLING 2016 • Chengyao Chen, Zhitao Wang, Yu Lei, Wenjie Li
The advantages of the proposed model is the ability to handle the semantic information and to learn two influence components including the opinion influence of the content information and the social relation factors.