research
∙
10/18/2022
Soft-Labeled Contrastive Pre-training for Function-level Code Representation
Code contrastive pre-training has recently achieved significant progress...
share
research
∙
09/30/2022
ASTF: Visual Abstractions of Time-Varying Patterns in Radio Signals
A time-frequency diagram is a commonly used visualization for observing ...
research
∙
08/13/2022
Attention Mechanism Based Intelligent Channel Feedback for mmWave Massive MIMO Systems
The potential advantages of intelligent wireless communications with mil...
research
∙
08/03/2022
Spectrum Focused Frequency Adversarial Attacks for Automatic Modulation Classification
Artificial intelligence (AI) technology has provided a potential solutio...
research
∙
07/14/2022
Few-Shot Specific Emitter Identification via Deep Metric Ensemble Learning
Specific emitter identification (SEI) is a highly potential technology f...
research
∙
06/24/2022
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Neural networks have been widely applied in security applications such a...
research
∙
03/21/2022
A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement
Recent years have seen the wide application of NLP models in crucial are...
research
∙
12/31/2021
Fast Graph Subset Selection Based on G-optimal Design
Graph sampling theory extends the traditional sampling theory to graphs ...
research
∙
12/31/2021
DeepVisualInsight: Time-Travelling Visualization for Spatio-Temporal Causality of Deep Classification Training
Understanding how the predictions of deep learning models are formed dur...
research
∙
10/06/2021
Generalizing Neural Networks by Reflecting Deviating Data in Production
Trained with a sufficiently large training and testing dataset, Deep Neu...
research
∙
09/25/2021
Constructing Regression Dataset from Code Evolution History
Bug datasets consisting of real-world bugs are important artifacts for r...
research
∙
03/03/2021
Self-Checking Deep Neural Networks in Deployment
The widespread adoption of Deep Neural Networks (DNNs) in important doma...
research
∙
06/18/2020
CoinWatch: A Clone-Based Approach For Detecting Vulnerabilities in Cryptocurrencies
Cryptocurrencies have become very popular in recent years. Thousands of ...
research
∙
04/18/2020
sFuzz: An Efficient Adaptive Fuzzer for Solidity Smart Contracts
Smart contracts are Turing-complete programs that execute on the infrast...
research
∙
04/10/2020
SR2CNN: Zero-Shot Learning for Signal Recognition
Signal recognition is one of significant and challenging tasks in the si...
research
∙
12/10/2019
Doublade: Unknown Vulnerability Detection in Smart Contracts Via Abstract Signature Matching and Refined Detection Rules
With the prosperity of smart contracts and the blockchain technology, va...
research
∙
11/29/2017
