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05/29/2023
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
Misalignment between the outputs of a vision-language (VL) model and tas...
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05/23/2023
CLIP4STR: A Simple Baseline for Scene Text Recognition with Pre-trained Vision-Language Model
Pre-trained vision-language models are the de-facto foundation models fo...
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05/02/2023
Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models
The prompt-based learning paradigm, which bridges the gap between pre-tr...
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03/02/2023
Evaluating Parameter-Efficient Transfer Learning Approaches on SURE Benchmark for Speech Understanding
Fine-tuning is widely used as the default algorithm for transfer learnin...
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01/02/2023
Fusing Models for Prognostics and Health Management of Lithium-Ion Batteries Based on Physics-Informed Neural Networks
For Prognostics and Health Management (PHM) of Lithium-ion (Li-ion) batt...
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12/08/2022
AutoPINN: When AutoML Meets Physics-Informed Neural Networks
Physics-Informed Neural Networks (PINNs) have recently been proposed to ...
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11/04/2022
A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data
The substitute-based recommendation is widely used in E-commerce to prov...
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10/22/2022
Generative Prompt Tuning for Relation Classification
Using prompts to explore the knowledge contained within pre-trained lang...
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09/30/2022
Slimmable Networks for Contrastive Self-supervised Learning
Self-supervised learning makes great progress in large model pre-trainin...
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08/29/2022
Latent Heterogeneous Graph Network for Incomplete Multi-View Learning
Multi-view learning has progressed rapidly in recent years. Although man...
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07/28/2022
Learning Personalized Representations using Graph Convolutional Network
Generating representations that precisely reflect customers' behavior is...
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05/30/2022
Analyzing Modality Robustness in Multimodal Sentiment Analysis
Building robust multimodal models are crucial for achieving reliable dep...
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05/04/2022
Exploring Entity Interactions for Few-Shot Relation Learning (Student Abstract)
Few-shot relation learning refers to infer facts for relations with a li...
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05/02/2022
CenterCLIP: Token Clustering for Efficient Text-Video Retrieval
Recently, large-scale pre-training methods like CLIP have made great pro...
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03/22/2022
WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models
Compared with the domain-specific model, the vision-language pre-trainin...
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09/22/2021
FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning
Despite the success of neural dialogue systems in achieving high perform...
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06/09/2021
Attacking Adversarial Attacks as A Defense
It is well known that adversarial attacks can fool deep neural networks ...
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04/01/2021
Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering
Question Answering (QA) models over Knowledge Bases (KBs) are capable of...
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03/10/2021
ES-Net: Erasing Salient Parts to Learn More in Re-Identification
As an instance-level recognition problem, re-identification (re-ID) requ...
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11/30/2020
SplitNet: Divide and Co-training
The width of a neural network matters since increasing the width will ne...
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10/10/2020
Accelerate Your CNN from Three Dimensions: A Comprehensive Pruning Framework
To deploy a pre-trained deep CNN on resource-constrained mobile devices,...
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09/10/2020
Multi-Objective Parameter-less Population Pyramid for Solving Industrial Process Planning Problems
Evolutionary methods are effective tools for obtaining high-quality resu...
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02/16/2020
To be Tough or Soft: Measuring the Impact of Counter-Ad-blocking Strategies on User Engagement
The fast growing ad-blocker usage results in large revenue decrease for ...
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01/04/2020
Adversarial-Learned Loss for Domain Adaptation
Recently, remarkable progress has been made in learning transferable rep...
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12/21/2019
DBP: Discrimination Based Block-Level Pruning for Deep Model Acceleration
Neural network pruning is one of the most popular methods of acceleratin...
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11/29/2019
Value-driven Manufacturing Planning using Cloud-based Evolutionary Optimisation
This paper considers manufacturing planning and scheduling of manufactur...
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10/26/2019
Region Mutual Information Loss for Semantic Segmentation
Semantic segmentation is a fundamental problem in computer vision. It is...
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10/19/2019
Correlation Maximized Structural Similarity Loss for Semantic Segmentation
Most semantic segmentation models treat semantic segmentation as a pixel...
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10/08/2019
An XML-based Factory Description Language for Smart Manufacturing Plants in Industry 4.0
Industry 4.0 revolution concerns the digital transformation of manufactu...
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10/08/2019
Integrated Process Planning and Scheduling in Commercial Smart Kitchens
This paper describes the possibility of applying a generic, cloud-based ...
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07/16/2019
Improving Semantic Segmentation via Dilated Affinity
Introducing explicit constraints on the structural predictions has been ...
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05/07/2019
Model Based System Assurance Using the Structured Assurance Case Metamodel
Assurance cases are used to demonstrate confidence in system properties ...
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10/16/2018