1 code implementation • 23 Apr 2024 • Muhammad Ahmad, Salvatore Distifano, Adil Mehmood Khan, Manuel Mazzara, Chenyu Li, Jing Yao, Hao Li, Jagannath Aryal, Jun Zhou, Gemine Vivone, Danfeng Hong
Traditional approaches encounter the curse of dimensionality, struggle with feature selection and extraction, lack spatial information consideration, exhibit limited robustness to noise, face scalability issues, and may not adapt well to complex data distributions.
no code implementations • 18 Apr 2024 • Zhihao Xu, Ruixuan Huang, Xiting Wang, Fangzhao Wu, Jing Yao, Xing Xie
Even when successful, the harmfulness of their outputs cannot be guaranteed, leading to suspicions that these methods have not accurately identified the safety vulnerabilities of LLMs.
1 code implementation • 12 Apr 2024 • Jing Yao, Danfeng Hong, Chenyu Li, Jocelyn Chanussot
Recurrent neural networks and Transformers have recently dominated most applications in hyperspectral (HS) imaging, owing to their capability to capture long-range dependencies from spectrum sequences.
no code implementations • 28 Mar 2024 • Yiyang Sun, Zhiyuan Xu, Xiaonian Wang, Jing Yao
To address these issues, existing approaches use additional semantic priori black-box networks to separate moving objects and improve the model only at the loss level.
1 code implementation • 11 Mar 2024 • Jianxun Lian, Yuxuan Lei, Xu Huang, Jing Yao, Wei Xu, Xing Xie
This paper introduces RecAI, a practical toolkit designed to augment or even revolutionize recommender systems with the advanced capabilities of Large Language Models (LLMs).
no code implementations • 7 Mar 2024 • Xinpeng Wang, Shitong Duan, Xiaoyuan Yi, Jing Yao, Shanlin Zhou, Zhihua Wei, Peng Zhang, Dongkuan Xu, Maosong Sun, Xing Xie
Big models have achieved revolutionary breakthroughs in the field of AI, but they might also pose potential concerns.
1 code implementation • 29 Feb 2024 • Yuxuan Lei, Jianxun Lian, Jing Yao, Mingqi Wu, Defu Lian, Xing Xie
Our empirical studies demonstrate that fine-tuning embedding models on the dataset leads to remarkable improvements in a variety of retrieval tasks.
no code implementations • 23 Feb 2024 • Chenyu Li, Bing Zhang, Danfeng Hong, Jing Yao, Jocelyn Chanussot
These factors also limit the performance of the well-known low-rank representation (LRR) models in terms of robustness on the separation of background and target features and the reliance on manual parameter selection.
no code implementations • 18 Nov 2023 • Yuxuan Lei, Jianxun Lian, Jing Yao, Xu Huang, Defu Lian, Xing Xie
Behavior alignment operates in the language space, representing user preferences and item information as text to learn the recommendation model's behavior; intention alignment works in the latent space of the recommendation model, using user and item representations to understand the model's behavior; hybrid alignment combines both language and latent spaces for alignment training.
no code implementations • 16 Nov 2023 • Jing Yao, Wei Xu, Jianxun Lian, Xiting Wang, Xiaoyuan Yi, Xing Xie
In this paper, we propose a general paradigm that augments LLMs with DOmain-specific KnowledgE to enhance their performance on practical applications, namely DOKE.
no code implementations • 15 Nov 2023 • Jing Yao, Xiaoyuan Yi, Xiting Wang, Yifan Gong, Xing Xie
The rapid advancement of Large Language Models (LLMs) has attracted much attention to value alignment for their responsible development.
no code implementations • 13 Nov 2023 • Danfeng Hong, Bing Zhang, Xuyang Li, YuXuan Li, Chenyu Li, Jing Yao, Naoto Yokoya, Hao Li, Pedram Ghamisi, Xiuping Jia, Antonio Plaza, Paolo Gamba, Jon Atli Benediktsson, Jocelyn Chanussot
The foundation model has recently garnered significant attention due to its potential to revolutionize the field of visual representation learning in a self-supervised manner.
no code implementations • 26 Oct 2023 • Xiaoyuan Yi, Jing Yao, Xiting Wang, Xing Xie
Big models have greatly advanced AI's ability to understand, generate, and manipulate information and content, enabling numerous applications.
no code implementations • 26 Sep 2023 • Danfeng Hong, Bing Zhang, Hao Li, YuXuan Li, Jing Yao, Chenyu Li, Martin Werner, Jocelyn Chanussot, Alexander Zipf, Xiao Xiang Zhu
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on individual urban environments (e. g., single cities or regions).
1 code implementation • 31 Aug 2023 • Xu Huang, Jianxun Lian, Yuxuan Lei, Jing Yao, Defu Lian, Xing Xie
In this paper, we bridge the gap between recommender models and LLMs, combining their respective strengths to create a versatile and interactive recommender system.
no code implementations • 23 Aug 2023 • Jing Yao, Xiaoyuan Yi, Xiting Wang, Jindong Wang, Xing Xie
Big models, exemplified by Large Language Models (LLMs), are models typically pre-trained on massive data and comprised of enormous parameters, which not only obtain significantly improved performance across diverse tasks but also present emergent capabilities absent in smaller models.
no code implementations • 2 Aug 2023 • Yiyang Sun, Xiaonian Wang, Yangyang Zhang, Jiagui Tang, Xiaqiang Tang, Jing Yao
Driving scene understanding is to obtain comprehensive scene information through the sensor data and provide a basis for downstream tasks, which is indispensable for the safety of self-driving vehicles.
1 code implementation • 27 Apr 2023 • Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang, Mingqi Wu, Lu Chen, Yunjun Gao, Xing Xie
In recent decades, there have been significant advancements in latent embedding-based CF methods for improved accuracy, such as matrix factorization, neural collaborative filtering, and LightGCN.
1 code implementation • 30 Nov 2022 • Jing Yao, Zheng Liu, Junhan Yang, Zhicheng Dou, Xing Xie, Ji-Rong Wen
In the first stage, a lightweight CNN-based ad-hod neighbor selector is deployed to filter useful neighbors for the matching task with a small computation cost.
1 code implementation • 11 Oct 2022 • Peitian Zhang, Zheng Liu, Shitao Xiao, Zhicheng Dou, Jing Yao
Based on comprehensive experiments on popular retrieval benchmarks, we verify that clusters and terms indeed complement each other, enabling HI$^2$ to achieve lossless retrieval quality with competitive efficiency across various index settings.
no code implementations • 19 Aug 2022 • Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Wu, Peitian Zhang, Ji-Rong Wen
In order to unify these two stages, we explore a model-based indexer for document retrieval.
no code implementations • 13 May 2022 • Minghua Wang, Danfeng Hong, Zhu Han, Jiaxin Li, Jing Yao, Lianru Gao, Bing Zhang, Jocelyn Chanussot
Owing to the rapid development of sensor technology, hyperspectral (HS) remote sensing (RS) imaging has provided a significant amount of spatial and spectral information for the observation and analysis of the Earth's surface at a distance of data acquisition devices, such as aircraft, spacecraft, and satellite.
1 code implementation • 7 May 2022 • Danfeng Hong, Jing Yao, Deyu Meng, Naoto Yokoya, Jocelyn Chanussot
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images.
Hyperspectral Image Super-Resolution Image Super-Resolution +1
no code implementations • 3 May 2022 • Jiaxin Li, Danfeng Hong, Lianru Gao, Jing Yao, Ke Zheng, Bing Zhang, Jocelyn Chanussot
With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily available nowadays, which renders researchers an opportunity to tackle current geoscience applications in a fresh way.
no code implementations • 1 Mar 2022 • Yujia Zhou, Jing Yao, Zhicheng Dou, Ledell Wu, Ji-Rong Wen
Web search provides a promising way for people to obtain information and has been extensively studied.
1 code implementation • 14 Feb 2022 • Jingwei Yi, Fangzhao Wu, Bin Zhu, Jing Yao, Zhulin Tao, Guangzhong Sun, Xing Xie
Our study reveals a critical security issue in existing federated news recommendation systems and calls for research efforts to address the issue.
1 code implementation • 14 Jan 2022 • Kai-Ni Wang, Xin Yang, Juzheng Miao, Lei LI, Jing Yao, Ping Zhou, Wufeng Xue, Guang-Quan Zhou, Xiahai Zhuang, Dong Ni
Extensive experimental results on a publicly available dataset from Myocardial pathology segmentation combining multi-sequence CMR (MyoPS 2020) demonstrate our method can achieve promising performance compared with other state-of-the-art methods.
no code implementations • 13 Oct 2021 • Peitian Zhang, Zhicheng Dou, Jing Yao
The key to personalized news recommendation is to match the user's interests with the candidate news precisely and efficiently.
no code implementations • 30 Sep 2021 • Jing Yao, Zhicheng Dou, Ruobing Xie, Yanxiong Lu, Zhiping Wang, Ji-Rong Wen
Search and recommendation are the two most common approaches used by people to obtain information.
2 code implementations • 7 Jul 2021 • Danfeng Hong, Zhu Han, Jing Yao, Lianru Gao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot
Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of materials by capturing subtle spectral discrepancies.
1 code implementation • 21 May 2021 • Danfeng Hong, Lianru Gao, Jing Yao, Naoto Yokoya, Jocelyn Chanussot, Uta Heiden, Bing Zhang
Over the past decades, enormous efforts have been made to improve the performance of linear or nonlinear mixing models for hyperspectral unmixing, yet their ability to simultaneously generalize various spectral variabilities and extract physically meaningful endmembers still remains limited due to the poor ability in data fitting and reconstruction and the sensitivity to various spectral variabilities.
1 code implementation • 21 May 2021 • Danfeng Hong, Jingliang Hu, Jing Yao, Jocelyn Chanussot, Xiao Xiang Zhu
Moreover, to better assess multimodal baselines and the newly-proposed S2FL model, three multimodal RS benchmark datasets, i. e., Houston2013 -- hyperspectral and multispectral data, Berlin -- hyperspectral and synthetic aperture radar (SAR) data, Augsburg -- hyperspectral, SAR, and digital surface model (DSM) data, are released and used for land cover classification.
no code implementations • 2 Mar 2021 • Danfeng Hong, wei he, Naoto Yokoya, Jing Yao, Lianru Gao, Liangpei Zhang, Jocelyn Chanussot, Xiao Xiang Zhu
Hyperspectral imaging, also known as image spectrometry, is a landmark technique in geoscience and remote sensing (RS).
2 code implementations • 15 Jan 2021 • Muhammad Ahmad, Sidrah Shabbir, Swalpa Kumar Roy, Danfeng Hong, Xin Wu, Jing Yao, Adil Mehmood Khan, Manuel Mazzara, Salvatore Distefano, Jocelyn Chanussot
Therefore, this survey discusses some strategies to improve the generalization performance of DL strategies which can provide some future guidelines.
no code implementations • 13 Sep 2020 • Haixia Bi, Jing Yao, Zhiqiang Wei, Danfeng Hong, Jocelyn Chanussot
Polarimetric synthetic aperture radar (PolSAR) image classification has been investigated vigorously in various remote sensing applications.
1 code implementation • 12 Aug 2020 • Danfeng Hong, Lianru Gao, Naoto Yokoya, Jing Yao, Jocelyn Chanussot, Qian Du, Bing Zhang
In particular, we also investigate a special case of multi-modality learning (MML) -- cross-modality learning (CML) that exists widely in RS image classification applications.
1 code implementation • 6 Aug 2020 • Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot
Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification, owing to their ability to capture spatial-spectral feature representations.
1 code implementation • 28 Jul 2020 • Lianru Gao, Danfeng Hong, Jing Yao, Bing Zhang, Paolo Gamba, Jocelyn Chanussot
However, the ability in the fusion of HS and MS images remains to be improved, particularly in large-scale scenes, due to the limited acquisition of HS images.
no code implementations • 17 Jul 2020 • Danfeng Hong, Jing Yao, Xin Wu, Jocelyn Chanussot, Xiao Xiang Zhu
In recent years, hyperspectral imaging, also known as imaging spectroscopy, has been paid an increasing interest in geoscience and remote sensing community.
1 code implementation • ECCV 2020 • Jing Yao, Danfeng Hong, Jocelyn Chanussot, Deyu Meng, Xiaoxiang Zhu, Zongben Xu
The recent advancement of deep learning techniques has made great progress on hyperspectral image super-resolution (HSI-SR).