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08/23/2023
OFVL-MS: Once for Visual Localization across Multiple Indoor Scenes
In this work, we seek to predict camera poses across scenes with a multi...
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08/09/2023
VulLibGen: Identifying Vulnerable Third-Party Libraries via Generative Pre-Trained Model
To avoid potential risks posed by vulnerabilities in third-party librari...
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07/31/2023
Poly-MOT: A Polyhedral Framework For 3D Multi-Object Tracking
3D Multi-object tracking (MOT) empowers mobile robots to accomplish well...
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07/17/2023
Identifying Vulnerable Third-Party Libraries from Textual Descriptions of Vulnerabilities and Libraries
To address security vulnerabilities arising from third-party libraries, ...
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02/13/2023
Reliability Assurance for Deep Neural Network Architectures Against Numerical Defects
With the widespread deployment of deep neural networks (DNNs), ensuring ...
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02/02/2023
Effective Random Test Generation for Deep Learning Compilers
Deep learning compilers help address difficulties of deploying deep lear...
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02/01/2023
CoderEval: A Benchmark of Pragmatic Code Generation with Generative Pre-trained Models
Code generation models based on the pre-training and fine-tuning paradig...
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01/10/2023
Practitioners' Expectations on Code Completion
Code completion has become a common practice for programmers during thei...
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01/08/2023
DeepMatcher: A Deep Transformer-based Network for Robust and Accurate Local Feature Matching
Local feature matching between images remains a challenging task, especi...
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06/17/2022
GDsmith: Detecting Bugs in Graph Database Engines
Graph database engines stand out in the era of big data for their effici...
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06/16/2022
Double Sampling Randomized Smoothing
Neural networks (NNs) are known to be vulnerable against adversarial per...
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08/01/2021
Groot: An Event-graph-based Approach for Root Cause Analysis in Industrial Settings
For large-scale distributed systems, it's crucial to efficiently diagnos...
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06/14/2021
No Free Lunch: Microservice Practices Reconsidered in Industry
Microservice architecture advocates a number of technologies and practic...
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02/12/2021
Speculating Ineffective UI Exploration via Trace Analysis
With the prosperity of mobile apps, quality assurance of mobile apps bec...
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09/09/2020
SoK: Certified Robustness for Deep Neural Networks
Great advancement in deep neural networks (DNNs) has led to state-of-the...
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09/08/2020
Adversarial Attack on Large Scale Graph
Recent studies have shown that graph neural networks are vulnerable agai...
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05/02/2020
Understanding Challenges in Deploying Deep Learning Based Software: An Empirical Study
Deep learning (DL) becomes increasingly pervasive, being used in a wide ...
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03/10/2020
A Survey of Adversarial Learning on Graphs
Deep learning models on graphs have achieved remarkable performance in v...
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02/27/2020
Provable Robust Learning Based on Transformation-Specific Smoothing
As machine learning systems become pervasive, safeguarding their securit...
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08/31/2018
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks
Despite being popularly used in many application domains such as image r...
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07/06/2018
Testing Untestable Neural Machine Translation: An Industrial Case
Neural Machine Translation (NMT) has been widely adopted recently due to...
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07/06/2018
Oracle-free Detection of Translation Issue for Neural Machine Translation
Neural Machine Translation (NMT) has been widely adopted over recent yea...
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07/06/2018
CoMID: Context-based Multi-Invariant Detection for Monitoring Cyber-Physical Software
Cyber-physical software continually interacts with its physical environm...
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11/27/2013