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Giri Krishnan

3 accepted papers

2024

Evaluation of Large Language Models on Code Obfuscation (Student Abstract)

AAAI 2024technical

Obfuscation intends to decrease interpretability of code and identification of code behavior. Large Language Models(LLMs) have been proposed for code synthesis and code analysis. This paper attempts to understand how well LLMs can analyse code and identify code behavior. Specifically, this paper sys…

2024

Sleep-Like Unsupervised Replay Improves Performance When Data Are Limited or Unbalanced (Student Abstract)

AAAI 2024technical

The performance of artificial neural networks (ANNs) degrades when training data are limited or imbalanced. In contrast, the human brain can learn quickly from just a few examples. Here, we investigated the role of sleep in improving the performance of ANNs trained with limited data on the MNIST and…

Cited by 1SourcePDFScholar
2020

Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks

ICLR 2020poster

Current artificial neural networks (ANNs) can perform and excel at a variety of tasks ranging from image classification to spam detection through training on large datasets of labeled data. While the trained network may perform well on similar testing data, inputs that differ even slightly from the…

Cited by 24SourceScholar