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09/13/2023
GelFlow: Self-supervised Learning of Optical Flow for Vision-Based Tactile Sensor Displacement Measurement
High-resolution multi-modality information acquired by vision-based tact...
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09/11/2023
Incorporating Pre-trained Model Prompting in Multimodal Stock Volume Movement Prediction
Multimodal stock trading volume movement prediction with stock-related n...
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06/22/2023
Continuous Layout Editing of Single Images with Diffusion Models
Recent advancements in large-scale text-to-image diffusion models have e...
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05/31/2023
TransAct: Transformer-based Realtime User Action Model for Recommendation at Pinterest
Sequential models that encode user activity for next action prediction h...
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05/08/2023
Diffusion Theory as a Scalpel: Detecting and Purifying Poisonous Dimensions in Pre-trained Language Models Caused by Backdoor or Bias
Pre-trained Language Models (PLMs) may be poisonous with backdoors or bi...
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11/07/2022
A mixed precision Jacobi method for the symmetric eigenvalue problem
The eigenvalue problem is a fundamental problem in scientific computing....
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10/26/2022
Learning a Task-specific Descriptor for Robust Matching of 3D Point Clouds
Existing learning-based point feature descriptors are usually task-agnos...
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10/26/2022
Searching Dense Point Correspondences via Permutation Matrix Learning
Although 3D point cloud data has received widespread attentions as a gen...
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10/18/2022
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
Deep Neural Networks (DNNs) are known to be vulnerable to backdoor attac...
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10/14/2022
Expose Backdoors on the Way: A Feature-Based Efficient Defense against Textual Backdoor Attacks
Natural language processing (NLP) models are known to be vulnerable to b...
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10/13/2022
GA-SAM: Gradient-Strength based Adaptive Sharpness-Aware Minimization for Improved Generalization
Recently, Sharpness-Aware Minimization (SAM) algorithm has shown state-o...
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10/13/2022
Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation
Despite the potential of federated learning, it is known to be vulnerabl...
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09/26/2022
Risk-Aware Model Predictive Path Integral Control Using Conditional Value-at-Risk
In this paper, we present a novel Model Predictive Control method for au...
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05/25/2022
Context-Aware Video Reconstruction for Rolling Shutter Cameras
With the ubiquity of rolling shutter (RS) cameras, it is becoming increa...
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05/10/2022
Iterative models for complex networks formed by extending cliques
We consider a new model for complex networks whose underlying mechanism ...
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03/24/2022
VRNet: Learning the Rectified Virtual Corresponding Points for 3D Point Cloud Registration
3D point cloud registration is fragile to outliers, which are labeled as...
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03/24/2022
A Representation Separation Perspective to Correspondences-free Unsupervised 3D Point Cloud Registration
3D point cloud registration in remote sensing field has been greatly adv...
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03/13/2022
CVFNet: Real-time 3D Object Detection by Learning Cross View Features
In recent years 3D object detection from LiDAR point clouds has made gre...
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02/26/2022
RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning
3D point clouds deep learning is a promising field of research that allo...
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10/28/2021
End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration
Even though considerable progress has been made in deep learning-based 3...
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09/24/2021
Improving Model Predictive Path Integral using Covariance Steering
This paper presents a novel control approach for autonomous systems oper...
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09/13/2021
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Recent pretrained language models extend from millions to billions of pa...
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09/07/2021
Adversarial Parameter Defense by Multi-Step Risk Minimization
Previous studies demonstrate DNNs' vulnerability to adversarial examples...
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09/03/2021
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
Since training a large-scale backdoored model from scratch requires a la...
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08/20/2021
ASAT: Adaptively Scaled Adversarial Training in Time Series
Adversarial training is a method for enhancing neural networks to improv...
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05/15/2021
Rethinking Skip Connection with Layer Normalization in Transformers and ResNets
Skip connection, is a widely-used technique to improve the performance a...
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03/29/2021
Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models
Recent studies have revealed a security threat to natural language proce...
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12/25/2020
Learning Robust Representation for Clustering through Locality Preserving Variational Discriminative Network
Clustering is one of the fundamental problems in unsupervised learning. ...
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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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08/07/2020
Global Context Aware Convolutions for 3D Point Cloud Understanding
Recent advances in deep learning for 3D point clouds have shown great pr...
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06/18/2020
Shop The Look: Building a Large Scale Visual Shopping System at Pinterest
As online content becomes ever more visual, the demand for searching by ...
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06/10/2020
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape?
The residual network is now one of the most effective structures in deep...
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06/10/2020
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption
We argue that the vulnerability of model parameters is of crucial value ...
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12/25/2019
Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection
Self-attention based Transformer has demonstrated the state-of-the-art p...
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11/17/2019
MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning
In sequence to sequence learning, the self-attention mechanism proves to...
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11/16/2019
Understanding and Improving Layer Normalization
Layer normalization (LayerNorm) is a technique to normalize the distribu...
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08/17/2019
Rotation Invariant Convolutions for 3D Point Clouds Deep Learning
Recent progresses in 3D deep learning has shown that it is possible to d...
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08/17/2019
ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics
Deep learning with 3D data has progressed significantly since the introd...
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07/05/2019
Forecasting security's volatility using low-frequency historical data, high-frequency historical data and option-implied volatility
Low-frequency historical data, high-frequency historical data and option...
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05/24/2019
Memorized Sparse Backpropagation
Neural network learning is typically slow since backpropagation needs to...
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08/14/2018
Primal Meaning Recommendation for Chinese Words and Phrases via Descriptions in On-line Encyclopedia
Polysemy is a very common phenomenon in modern languages. Most of previo...
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03/05/2018
Automatic Transferring between Ancient Chinese and Contemporary Chinese
During the long time of development, Chinese language has evolved a grea...
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01/20/2018