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09/20/2023
Long-tail Augmented Graph Contrastive Learning for Recommendation
Graph Convolutional Networks (GCNs) has demonstrated promising results f...
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09/06/2023
Enhancing Event Sequence Modeling with Contrastive Relational Inference
Neural temporal point processes(TPPs) have shown promise for modeling co...
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08/31/2023
AntM^2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction
Click-through rate (CTR) prediction is a crucial issue in recommendation...
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08/21/2023
Enhancing Recommender Systems with Large Language Model Reasoning Graphs
Recommendation systems aim to provide users with relevant suggestions, b...
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08/17/2023
Fine-grained Text and Image Guided Point Cloud Completion with CLIP Model
This paper focuses on the recently popular task of point cloud completio...
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08/10/2023
Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimation
One critical challenge in 6D object pose estimation from a single RGBD i...
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07/29/2023
Continual Learning in Predictive Autoscaling
Predictive Autoscaling is used to forecast the workloads of servers and ...
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07/18/2023
Efficient Region-Aware Neural Radiance Fields for High-Fidelity Talking Portrait Synthesis
This paper presents ER-NeRF, a novel conditional Neural Radiance Fields ...
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07/18/2023
Federated Large Language Model: A Position Paper
Large scale language models (LLM) have received significant attention an...
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06/20/2023
Deep Double Self-Expressive Subspace Clustering
Deep subspace clustering based on auto-encoder has received wide attenti...
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06/19/2023
RemoteCLIP: A Vision Language Foundation Model for Remote Sensing
General-purpose foundation models have become increasingly important in ...
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05/19/2023
ALT: An Automatic System for Long Tail Scenario Modeling
In this paper, we consider the problem of long tail scenario modeling wi...
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04/30/2023
Few-shot Classification via Ensemble Learning with Multi-Order Statistics
Transfer learning has been widely adopted for few-shot classification. R...
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04/25/2023
COUPA: An Industrial Recommender System for Online to Offline Service Platforms
Aiming at helping users locally discovery retail services (e.g., enterta...
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04/25/2023
GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning
Recently, the growth of service platforms brings great convenience to bo...
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03/27/2023
Towards Open Temporal Graph Neural Networks
Graph neural networks (GNNs) for temporal graphs have recently attracted...
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02/16/2023
Spectral 3D Computer Vision – A Review
Spectral 3D computer vision examines both the geometric and spectral pro...
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02/13/2023
DCMT: A Direct Entire-Space Causal Multi-Task Framework for Post-Click Conversion Estimation
In recommendation scenarios, there are two long-standing challenges, i.e...
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02/10/2023
GCNet: Probing Self-Similarity Learning for Generalized Counting Network
The class-agnostic counting (CAC) problem has caught increasing attentio...
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11/01/2022
Robust Direct Learning for Causal Data Fusion
In the era of big data, the explosive growth of multi-source heterogeneo...
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10/27/2022
Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks
Spiking neural networks (SNNs) are well suited for resource-constrained ...
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10/24/2022
A Practical Distributed ADMM Solver for Billion-Scale Generalized Assignment Problems
Assigning items to owners is a common problem found in various real-worl...
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10/11/2022
PP-StructureV2: A Stronger Document Analysis System
A large amount of document data exists in unstructured form such as raw ...
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08/18/2022
GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search
Current Graph Neural Networks (GNNs) suffer from the over-smoothing prob...
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08/17/2022
Ask Question First for Enhancing Lifelong Language Learning
Lifelong language learning aims to stream learning NLP tasks while retai...
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08/17/2022
SO(3)-Pose: SO(3)-Equivariance Learning for 6D Object Pose Estimation
6D pose estimation of rigid objects from RGB-D images is crucial for obj...
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08/17/2022
AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach
Graph anomaly detection on attributed networks has become a prevalent re...
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07/27/2022
Gaia: Graph Neural Network with Temporal Shift aware Attention for Gross Merchandise Value Forecast in E-commerce
E-commerce has gone a long way in empowering merchants through the inter...
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06/23/2022
Agriculture-Vision Challenge 2022 – The Runner-Up Solution for Agricultural Pattern Recognition via Transformer-based Models
The Agriculture-Vision Challenge in CVPR is one of the most famous and c...
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05/28/2022
BadDet: Backdoor Attacks on Object Detection
Deep learning models have been deployed in numerous real-world applicati...
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05/22/2022
RVAE-LAMOL: Residual Variational Autoencoder to Enhance Lifelong Language Learning
Lifelong Language Learning (LLL) aims to train a neural network to learn...
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05/17/2022
KGNN: Distributed Framework for Graph Neural Knowledge Representation
Knowledge representation learning has been commonly adopted to incorpora...
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04/07/2022
Transfer Attacks Revisited: A Large-Scale Empirical Study in Real Computer Vision Settings
One intriguing property of adversarial attacks is their "transferability...
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03/15/2022
CrowdMLP: Weakly-Supervised Crowd Counting via Multi-Granularity MLP
Existing state-of-the-art crowd counting algorithms rely excessively on ...
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03/03/2022
Neural Graph Matching for Pre-training Graph Neural Networks
Recently, graph neural networks (GNNs) have been shown powerful capacity...
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03/01/2022
An Effective Graph Learning based Approach for Temporal Link Prediction: The First Place of WSDM Cup 2022
Temporal link prediction, as one of the most crucial work in temporal gr...
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01/27/2022
Confidence May Cheat: Self-Training on Graph Neural Networks under Distribution Shift
Graph Convolutional Networks (GCNs) have recently attracted vast interes...
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01/21/2022
Robust Unsupervised Graph Representation Learning via Mutual Information Maximization
Recent studies have shown that GNNs are vulnerable to adversarial attack...
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12/28/2021
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback
In federated learning (FL) problems, client sampling plays a key role in...
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11/22/2021
Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records
There is a continuously growing demand for emergency department (ED) ser...
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11/03/2021
Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation
Knowledge graph is generally incorporated into recommender systems to im...
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10/27/2021
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data
Time series forecasting is widely used in business intelligence, e.g., f...
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10/26/2021
Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable
Multi-hop QA requires the machine to answer complex questions through fi...
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10/22/2021
PPSGCN: A Privacy-Preserving Subgraph Sampling Based Distributed GCN Training Method
Graph convolutional networks (GCNs) have been widely adopted for graph r...
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10/17/2021
Reminding the Incremental Language Model via Data-Free Self-Distillation
Incremental language learning with pseudo-data can alleviate catastrophi...
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09/07/2021
PP-OCRv2: Bag of Tricks for Ultra Lightweight OCR System
Optical Character Recognition (OCR) systems have been widely used in var...
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08/18/2021
SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation
Recent studies in recommender systems have managed to achieve significan...
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08/18/2021
A Unified Framework for Cross-Domain and Cross-System Recommendations
Cross-Domain Recommendation (CDR) and Cross-System Recommendation (CSR) ...
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06/29/2021
Improving Transferability of Adversarial Patches on Face Recognition with Generative Models
Face recognition is greatly improved by deep convolutional neural networ...
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06/09/2021