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Found 15 papers, 6 papers with code
What is Meant by AGI? On the Definition of Artificial General Intelligence
This paper aims to establish a consensus on AGI's definition.
Patched Line Segment Learning for Vector Road Mapping
In our experiments, we demonstrate how an effective representation of a road graph significantly enhances the performance of vector road mapping on established benchmarks, without requiring extensive modifications to the neural network architecture.
A Brain-Inspired Sequence Learning Model based on a Logic
In Artificial Intelligence, sequence prediction task is usually used to test a sequence learning model.
Multi-Granularity Detector for Vulnerability Fixes
To address these challenges and boost the effectiveness of prior works, we propose MiDas (Multi-Granularity Detector for Vulnerability Fixes).
Simulation of Non-inductive Vector Control of Permanent Magnet Synchronous Motor Based on Sliding Mode Observer
In this study, a mathematical model for sensorless control of a PMSM is developed using SMO, vector control, and other techniques.
Minimal-time Deadbeat Consensus and Individual Disagreement Degree Prediction for High-order Linear Multi-agent Systems
Sufficient conditions are derived to guarantee both the minimal-time deadbeat consensus and the instant individual disagreement degree prediction.
A Study of Variable-Role-based Feature Enrichment in Neural Models of Code
In this paper, we explore the impact of an unsuperivsed feature enrichment approach based on variable roles on the performance of neural models of code.
Efficient Teacher: Semi-Supervised Object Detection for YOLOv5
The Pseudo Label Assigner prevents the occurrence of bias caused by a large number of low-quality pseudo labels that may interfere with the Dense Detector during the student-teacher mutual learning mechanism, and the Epoch Adaptor utilizes domain and distribution adaptation to allow Dense Detector to learn globally distributed consistent features, making the training independent of the proportion of labeled data.
BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets
Our experiments conducted on four tasks and four offline RL algorithms expose a disquieting fact: none of the existing offline RL algorithms is immune to such a backdoor attack.
Accurate Polygonal Mapping of Buildings in Satellite Imagery
We addressed such an issue by exploiting the hierarchical supervision (of bottom-level vertices, mid-level line segments and the high-level regional masks) and proposed a novel interaction mechanism of feature embedding sourced from different levels of supervision signals to obtain reversible building masks for polygonal mapping of buildings.
Artificial Open World for Evaluating AGI: a Conceptual Design
However, once a developer tests and debugs the agent with a problem, the never-encountered problem becomes the encountered problem, as a result, the problem is solved by the developers to some extent, exploiting their experience, rather than the agents.
Detecting False Data Injection Attacks in Smart Grids with Modeling Errors: A Deep Transfer Learning Based Approach
In this paper, an illustrative case has revealed that modeling errors in transmission lines significantly weaken the detection effectiveness of conventional FDIA approaches.
4D Attention-based Neural Network for EEG Emotion Recognition
The experimental results have shown the effectiveness of the attention mechanisms in different domains for EEG emotion recognition.
Ranked #1 on
Emotion Recognition
on SEED
Question Relatedness on Stack Overflow: The Task, Dataset, and Corpus-inspired Models
The proposed dataset Stack Overflow is a useful resource to develop novel solutions, specifically data-hungry neural network models, for the prediction of relatedness in technical community question-answering forums.
Three Mechanisms of Weight Decay Regularization
Weight decay is one of the standard tricks in the neural network toolbox, but the reasons for its regularization effect are poorly understood, and recent results have cast doubt on the traditional interpretation in terms of $L_2$ regularization.
