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09/18/2023
Causal-Story: Local Causal Attention Utilizing Parameter-Efficient Tuning For Visual Story Synthesis
The excellent text-to-image synthesis capability of diffusion models has...
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08/16/2023
Improving Depth Gradient Continuity in Transformers: A Comparative Study on Monocular Depth Estimation with CNN
Monocular depth estimation is an ongoing challenge in computer vision. R...
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07/31/2023
FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis
In this paper, we propose FinVis-GPT, a novel multimodal large language ...
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07/31/2023
An Effective Data Creation Pipeline to Generate High-quality Financial Instruction Data for Large Language Model
At the beginning era of large language model, it is quite critical to ge...
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07/06/2023
BrickPal: Augmented Reality-based Assembly Instructions for Brick Models
The assembly instruction is a mandatory component of Lego-like brick set...
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06/17/2023
Enlighten Anything: When Segment Anything Model Meets Low-Light Image Enhancement
Image restoration is a low-level visual task, and most CNN methods are d...
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01/24/2023
Transformer-Patcher: One Mistake worth One Neuron
Large Transformer-based Pretrained Language Models (PLMs) dominate almos...
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10/11/2022
Mixture of Attention Heads: Selecting Attention Heads Per Token
Mixture-of-Experts (MoE) networks have been proposed as an efficient way...
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08/12/2022
GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs
Heterogeneous graphs, which contain nodes and edges of multiple types, a...
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12/29/2021
VDPC: Variational Density Peak Clustering Algorithm
The widely applied density peak clustering (DPC) algorithm makes an intu...
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09/05/2021
Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
Community detection, aiming to group the graph nodes into clusters with ...
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05/30/2021
DAGNN: Demand-aware Graph Neural Networks for Session-based Recommendation
Session-based recommendations have been widely adopted for various onlin...
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04/13/2021
Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning
Graph representation learning has long been an important yet challenging...
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11/25/2020
RRCN: A Reinforced Random Convolutional Network based Reciprocal Recommendation Approach for Online Dating
Recently, the reciprocal recommendation, especially for online dating ap...
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10/23/2020
Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation
Automatically generating financial report from a piece of news is quite ...
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07/08/2020
SiENet: Siamese Expansion Network for Image Extrapolation
Different from image inpainting, image outpainting has relative less con...
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11/21/2019
Automatically Generating Macro Research Reports from a Piece of News
Automatically generating macro research reports from economic news is an...
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11/20/2019
Computer-Aided Clinical Skin Disease Diagnosis Using CNN and Object Detection Models
Skin disease is one of the most common types of human diseases, which ma...
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10/22/2019
Structure Matters: Towards Generating Transferable Adversarial Images
Recent works on adversarial examples for image classification focus on d...
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09/23/2019
Heterogeneous Graph Convolutional Networks for Temporal Community Detection
The Graph Convolutional Networks (GCN) has demonstrated superior perform...
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09/15/2018
Wasserstein Autoencoders for Collaborative Filtering
The recommender systems have long been investigated in the literature. R...
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09/08/2018
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples
Adversarial examples are perturbed inputs designed to fool machine learn...
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08/29/2018
DADA: Deep Adversarial Data Augmentation for Extremely Low Data Regime Classification
Deep learning has revolutionized the performance of classification, but ...
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05/01/2017