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09/14/2023
MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
Starting from the resurgence of deep learning, vision-language models (V...
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09/05/2023
Making Large Language Models Better Reasoners with Alignment
Reasoning is a cognitive process of using evidence to reach a sound conc...
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08/22/2023
Domain Generalization via Rationale Invariance
This paper offers a new perspective to ease the challenge of domain gene...
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08/13/2023
SAILOR: Structural Augmentation Based Tail Node Representation Learning
Graph Neural Networks (GNNs) have achieved state-of-the-art performance ...
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08/10/2023
Deep Richardson-Lucy Deconvolution for Low-Light Image Deblurring
Images taken under the low-light condition often contain blur and satura...
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06/07/2023
M^3IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning
Instruction tuning has significantly advanced large language models (LLM...
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06/03/2023
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning
Oversmoothing is a common phenomenon in graph neural networks (GNNs), in...
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05/30/2023
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
While contrastive self-supervised learning has become the de-facto learn...
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05/29/2023
Large Language Models are not Fair Evaluators
We uncover a systematic bias in the evaluation paradigm of adopting larg...
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05/26/2023
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
The rapid development of digital economy has led to the emergence of var...
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05/25/2023
TransWorldNG: Traffic Simulation via Foundation Model
Traffic simulation is a crucial tool for transportation decision-making ...
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05/24/2023
Building Transportation Foundation Model via Generative Graph Transformer
Efficient traffic management is crucial for maintaining urban mobility, ...
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05/23/2023
On the robust learning mixtures of linear regressions
In this note, we consider the problem of robust learning mixtures of lin...
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05/23/2023
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Anomaly detection aims to distinguish abnormal instances that deviate si...
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05/22/2023
Towards Robust Personalized Dialogue Generation via Order-Insensitive Representation Regularization
Generating persona consistent dialogue response is important for develop...
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05/18/2023
On the Off-Target Problem of Zero-Shot Multilingual Neural Machine Translation
While multilingual neural machine translation has achieved great success...
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05/18/2023
Less Can Be More: Unsupervised Graph Pruning for Large-scale Dynamic Graphs
The prevalence of large-scale graphs poses great challenges in time and ...
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04/25/2023
Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing
Multi-task learning for various real-world applications usually involves...
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04/24/2023
Efficient Halftoning via Deep Reinforcement Learning
Halftoning aims to reproduce a continuous-tone image with pixels whose i...
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04/13/2023
Cross-View Hierarchy Network for Stereo Image Super-Resolution
Stereo image super-resolution aims to improve the quality of high-resolu...
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04/12/2023
Stochastic Domain Decomposition Based on Variable-Separation Method
Uncertainty propagation across different domains is of fundamental impor...
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04/10/2023
Improved Test-Time Adaptation for Domain Generalization
The main challenge in domain generalization (DG) is to handle the distri...
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04/06/2023
On the Pareto Front of Multilingual Neural Machine Translation
In this work, we study how the generalization performance of a given dir...
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04/06/2023
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures
Federated Recommender Systems (FedRecs) are considered privacy-preservin...
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02/07/2023
Self-Sampling Training and Evaluation for the Accuracy-Bias Tradeoff in Recommendation
Research on debiased recommendation has shown promising results. However...
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01/26/2023
Optimizing Feature Set for Click-Through Rate Prediction
Click-through prediction (CTR) models transform features into latent vec...
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01/11/2023
CARD: Semantic Segmentation with Efficient Class-Aware Regularized Decoder
Semantic segmentation has recently achieved notable advances by exploiti...
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12/23/2022
A Cut-and-solve Algorithm for Virtual Machine Consolidation Problem
The virtual machine consolidation problem (VMCP) attempts to determine w...
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11/20/2022
Spectral Adversarial Training for Robust Graph Neural Network
Recent studies demonstrate that Graph Neural Networks (GNNs) are vulnera...
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11/09/2022
Are All Edges Necessary? A Unified Framework for Graph Purification
Graph Neural Networks (GNNs) as deep learning models working on graph-st...
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10/20/2022
Large-batch Optimization for Dense Visual Predictions
Training a large-scale deep neural network in a large-scale dataset is c...
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10/06/2022
A Coupled Hybridizable Discontinuous Galerkin and Boundary Integral Method for Analyzing Electromagnetic Scattering
A coupled hybridizable discontinuous Galerkin (HDG) and boundary integra...
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09/29/2022
A Two-Stage Method for Chinese AMR Parsing
In this paper, we provide a detailed description of our system at CAMRP-...
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08/15/2022
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
Recent years have seen a surge in research on dynamic graph representati...
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05/20/2022
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders
We present masked graph autoencoder (MaskGAE), a self-supervised learnin...
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05/20/2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection
Deep graph learning has achieved remarkable progresses in both business ...
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05/05/2022
Spiking Graph Convolutional Networks
Graph Convolutional Networks (GCNs) achieve an impressive performance du...
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05/03/2022
A Survey of Deep Learning Models for Structural Code Understanding
In recent years, the rise of deep learning and automation requirements i...
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05/02/2022
FastGCL: Fast Self-Supervised Learning on Graphs via Contrastive Neighborhood Aggregation
Graph contrastive learning (GCL), as a popular approach to graph self-su...
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04/20/2022
GUARD: Graph Universal Adversarial Defense
Recently, graph convolutional networks (GCNs) have shown to be vulnerabl...
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04/19/2022
Self-Calibrated Efficient Transformer for Lightweight Super-Resolution
Recently, deep learning has been successfully applied to the single-imag...
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04/19/2022
ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs
As Abstract Meaning Representation (AMR) implicitly involves compound se...
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03/23/2022
Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection
Recent studies in deepfake detection have yielded promising results when...
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03/14/2022
CAR: Class-aware Regularizations for Semantic Segmentation
Recent segmentation methods, such as OCR and CPNet, utilizing "class lev...
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03/06/2022
Focus on the Target's Vocabulary: Masked Label Smoothing for Machine Translation
Label smoothing and vocabulary sharing are two widely used techniques in...
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02/25/2022
Faithful learning with sure data for lung nodule diagnosis
Recent evolution in deep learning has proven its value for CT-based lung...
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02/17/2022
Enhanced DeepONet for Modeling Partial Differential Operators Considering Multiple Input Functions
Machine learning, especially deep learning is gaining much attention due...
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02/15/2022
Recent Advances in Reliable Deep Graph Learning: Adversarial Attack, Inherent Noise, and Distribution Shift
Deep graph learning (DGL) has achieved remarkable progress in both busin...
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11/18/2021
Perceiving and Modeling Density is All You Need for Image Dehazing
In the real world, the degradation of images taken under haze can be qui...
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10/15/2021
