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Found 7 papers, 1 papers with code
Learning a Decision Tree Algorithm with Transformers
We then train MetaTree to produce the trees that achieve strong generalization performance.
WavSpA: Wavelet Space Attention for Boosting Transformers' Long Sequence Learning Ability
Recent works show that learning attention in the Fourier space can improve the long sequence learning capability of Transformers.
Data-Driven AI Model Signal-Awareness Enhancement and Introspection
AI modeling for source code understanding tasks has been making significant progress, and is being adopted in production development pipelines.
Software Vulnerability Detection via Deep Learning over Disaggregated Code Graph Representation
Identifying vulnerable code is a precautionary measure to counter software security breaches.
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization
We measure the signal awareness of models using a new metric we propose- Signal-aware Recall (SAR).
Exploring Software Naturalness through Neural Language Models
We explore this hypothesis through the use of a pre-trained transformer-based language model to perform code analysis tasks.
Learning to map source code to software vulnerability using code-as-a-graph
We explore the applicability of Graph Neural Networks in learning the nuances of source code from a security perspective.
