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Found 7 papers, 2 papers with code
On Trojan Signatures in Large Language Models of Code
Trojan signatures, as described by Fields et al. (2021), are noticeable differences in the distribution of the trojaned class parameters (weights) and the non-trojaned class parameters of the trojaned model, that can be used to detect the trojaned model.
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.
Study of Distractors in Neural Models of Code
Understanding distractors provide a complementary view of the features' relevance in the predictions of neural models.
Co-channel Interference Management for the Next-Generation Heterogeneous Networks using Deep Leaning
Therefore, if radio access channels are shared, utilization of DL-based FeICIC and CoMP for coordinated scheduling gives the best performance.
Syntax-Guided Program Reduction for Understanding Neural Code Intelligence Models
Our experiments on multiple models across different types of input programs show that the syntax-guided program reduction technique is faster and provides smaller sets of key tokens in reduced programs.
Testing the Robustness of a BiLSTM-based Structural Story Classifier
The growing prevalence of counterfeit stories on the internet has fostered significant interest towards fast and scalable detection of fake news in the machine learning community.
Memorization and Generalization in Neural Code Intelligence Models
The goal of this paper is to evaluate and compare the extent of memorization and generalization in neural code intelligence models.
