Search Results for author: Jing Yao

Found 40 papers, 20 papers with code

CLAVE: An Adaptive Framework for Evaluating Values of LLM Generated Responses

no code implementations15 Jul 2024 Jing Yao, Xiaoyuan Yi, Xing Xie

The rapid progress in Large Language Models (LLMs) poses potential risks such as generating unethical content.

A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers

1 code implementation23 Apr 2024 Muhammad Ahmad, Salvatore Distifano, Adil Mehmood Khan, Manuel Mazzara, Chenyu Li, Jing Yao, Hao Li, Jagannath Aryal, 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.

Classification feature selection +2

SpectralMamba: Efficient Mamba for Hyperspectral Image Classification

1 code implementation12 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.

Classification Hyperspectral Image Classification +1

FlowDepth: Decoupling Optical Flow for Self-Supervised Monocular Depth Estimation

no code implementations28 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.

Monocular Depth Estimation Optical Flow Estimation

RecAI: Leveraging Large Language Models for Next-Generation Recommender Systems

1 code implementation11 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).

AI Agent Recommendation Systems

Aligning Language Models for Versatile Text-based Item Retrieval

1 code implementation29 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.

Retrieval

Low-Rank Representations Meets Deep Unfolding: A Generalized and Interpretable Network for Hyperspectral Anomaly Detection

no code implementations23 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.

Anomaly Detection

RecExplainer: Aligning Large Language Models for Explaining Recommendation Models

1 code implementation18 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 mimic the target 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.

Explanation Generation Instruction Following +2

Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations

no code implementations16 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.

Collaborative Filtering Recommendation Systems +1

Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values

no code implementations15 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.

Fairness

SpectralGPT: Spectral Remote Sensing Foundation Model

no code implementations13 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.

Change Detection Representation Learning +3

Unpacking the Ethical Value Alignment in Big Models

no code implementations26 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.

Ethics

Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks

no code implementations26 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).

Domain Adaptation Segmentation +1

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

1 code implementation31 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.

AI Agent Recommendation Systems +1

From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Models

no code implementations23 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.

Interpretable End-to-End Driving Model for Implicit Scene Understanding

no code implementations2 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.

Graph Generation object-detection +3

Towards Explainable Collaborative Filtering with Taste Clusters Learning

1 code implementation27 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.

Collaborative Filtering Decision Making +3

CDSM: Cascaded Deep Semantic Matching on Textual Graphs Leveraging Ad-hoc Neighbor Selection

1 code implementation30 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.

Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval

1 code implementation11 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.

Knowledge Distillation Quantization +1

Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer

no code implementations19 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.

Retrieval

Tensor Decompositions for Hyperspectral Data Processing in Remote Sensing: A Comprehensive Review

no code implementations13 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.

Anomaly Detection Super-Resolution +1

Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image Super-Resolution with Subpixel Fusion

1 code implementation7 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

Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review

no code implementations3 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.

Earth Observation

UA-FedRec: Untargeted Attack on Federated News Recommendation

1 code implementation14 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.

Federated Learning News Recommendation +2

AWSnet: An Auto-weighted Supervision Attention Network for Myocardial Scar and Edema Segmentation in Multi-sequence Cardiac Magnetic Resonance Images

1 code implementation14 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.

Segmentation

Learning to Select Historical News Articles for Interaction based Neural News Recommendation

no code implementations13 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.

News Recommendation

SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers

2 code implementations7 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.

Classification Hyperspectral Image Classification

Endmember-Guided Unmixing Network (EGU-Net): A General Deep Learning Framework for Self-Supervised Hyperspectral Unmixing

1 code implementation21 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.

Hyperspectral Unmixing

Multimodal Remote Sensing Benchmark Datasets for Land Cover Classification with A Shared and Specific Feature Learning Model

1 code implementation21 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.

Land Cover Classification

Interpretable Hyperspectral AI: When Non-Convex Modeling meets Hyperspectral Remote Sensing

no code implementations2 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).

PolSAR Image Classification Based on Robust Low-Rank Feature Extraction and Markov Random Field

no code implementations13 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.

Classification Data Augmentation +2

More Diverse Means Better: Multimodal Deep Learning Meets Remote Sensing Imagery Classification

1 code implementation12 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.

Classification General Classification +2

Graph Convolutional Networks for Hyperspectral Image Classification

1 code implementation6 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.

Classification General Classification +1

Spectral Superresolution of Multispectral Imagery with Joint Sparse and Low-Rank Learning

1 code implementation28 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.

Spatial-Spectral Manifold Embedding of Hyperspectral Data

no code implementations17 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.

Cannot find the paper you are looking for? You can Submit a new open access paper.